Miracle-dz/UniFAR-FTUs huggingface dataset:
Credit Risk Model Taking Account of Inflation and Its Contribution to Macroeconomic Discussion on Effect of Inflation on Output Growth

We use Extended Merton model (EMM) for estimating the firm’s credit risks in the presence of inflation. We show quantitatively that inflation is an influential factor making either a benign or adverse effect on the firm’s survival, supporting at the microeconomic level New Keynesian findings of the nonlinear inflation effect on output growth. Lower inflation increasing the firm’s expected rate of return can raise its mean year returns and decrease its default probability. Higher inflation, decreasing the expected rate return, makes the opposite effect. The magnitude of the adverse effect depends on the firm strength: for a steady firm, this effect is small, whereas for a weaker firm, it can be fatal. EMM is the only model taking account of inflation. It can be useful for banks or insurance companies estimating credit risks of commercial borrowers over the debt maturity, and for the firm’s management planning long-term business operations.
Analysis of Factors Affecting Gillnet Fisherman Income <10 GT at Fish Auction Place, Indramayu Regency

The purpose of this study is to analyze the income level of gillnet fishermen <10 GT, to analyze the factors that affect the level of income, and to formulate strategies and solutions to increase income. This research was conducted at the Fish Auction Place (TPI) Pabean Udik, Pabean Udik Village, Indramayu Regency. This location was chosen because the Udik Customs Fish Auction Place (TPI) is dominated by fishermen using gillnet fishing gear who have vessels <10 GT. The method used is the census method with samples taken as a whole. The analysis used in this research is the Logistic Regression Analysis and the SWOT Analysis. Research results obtained by using IBM SPSS, namely for the Sig Value Variable in the Equation is 100%, this value is interpreted by 8 (factors) Independent variables can affect income only educational factors that do not affect income and for the results obtained from SWOT analysis namely to increase the income of gillnet fishermen <10 GT at TPI Pabean Udik, namely the development of technology and fisheries business scale, development of access to capital for fishermen, development of marketing access, development of facilities and infrastructure at TPI Pabean Udik, Development of diversification of fish management and environmentally friendly fisheries management.
On the oxygenation of the Archaean and Proterozoic oceans

Abstract Modern-day ocean circulation behaves as a complex forced convective system that is characterized by the decrease in water temperature but increase in water density with depth. The dissolved oxygen content – which initially decreases due to biological oxygen demand – also increases with depth. In contrast to the present-day scenario, we propose that during the Archaean and Proterozoic eons inverted profiles could have developed such that, with depth, ocean water temperature increased and density and dissolved oxygen decreased. These inverted temperature and density profiles resulted in palaeo-ocean circulation behaving as a free convective system. It is proposed that this free convection, which may have been stable, or chaotic and subject to secondary instabilities, hindered the deep oxygenation of the palaeo-ocean. It may not be coincidental that the great oxygenation event (GOE) and Huronian glaciations are contemporaneous, in a similar way that the Neoproterozoic oxygenation event (NOE) is known to have been associated with glaciations. The global-scale external forcing required to switch the natural convective system to its present-day configuration is suggested to have been associated with Neoproterozoic glaciations and the subsequent lowering of ocean water salinity that accompanied them. We propose that this inverted the ocean water density gradient, allowing the oxygenation of the oceans for the first time. It is beyond the scope of this work to model the complex natural convection system, but we hope that geophysicists and numerical modellers will quantitatively evaluate the hypothesis proposed here to validate or refute our proposition.
Sintering behavior, structural phase transition, and microwave dielectric properties of La1‐xZnxTiNbO6‐x/2 ceramics

La1-xZnxTiNbO6-x/2 (LZTN-x) ceramics were prepared via a conventional solid-state reaction route. The phase, microstructure, sintering behavior, and microwave dielectric properties have been systematically studied. The substitution of a small amount of Zn2+ for La3+ was found to effectively promote the sintering process of LTN ceramics. The corresponding sintering mechanism was believed to result from the formation of the lattice distortion and oxygen vacancies by means of comparative studies on La-deficient LTN ceramics and 0.5 mol% ZnO added LTN ceramics (LTN+0.005ZnO). The resultant microwave dielectric properties of LTN ceramics were closely correlated with the sample density, compositions, and especially with the phase structure at room temperature which depended on the orthorhombic-monoclinic phase transition temperature and the sintering temperature. A single orthorhombic LZTN-0.03 ceramic sintered at 1200°C was achieved with good microwave dielectric properties of er~63, Q×f~9600 GHz (@4.77 GHz) and τf ~105 ppm/°C. By comparison, a relatively high Q × f~80995 GHz (@7.40 GHz) together with er~23, and τf ~−56 ppm/°C was obtained in monoclinic LTN+0.005ZnO ceramics sintered at 1350°C.
Fullerene-Nitroxide Derivatives as Potential Polarizers for Dynamic Nuclear Polarization (DNP) in Liquid State

Nuclear magnetic resonance spectroscopy and imaging (NMR/MRI) are widely applied methods for non-destructive analysis of biological systems, materials and medical applications. Dynamic nuclear polarization (DNP) is a method to enhance NMR signal by means of polarization transfer from unpaired electrons to nuclei through saturation the electron spin transition by microwave (MW). DNP in liquids is governed by Overhauser mechanism which results from the simultaneous flipping of electron and nuclear spins. The DNP efficiency decreases with increasing an external magnetic field. Since many organic molecules, which are potentially interesting for DNP as polarizers, are not soluble in water, the Overhauser DNP analysis has been done for toluene solutions. Also nonpolar solvents, in contrast to water, suffer less from dielectric losses and this allows using larger volume of the investigated samples. These experiments have demonstrated higher DNP efficiency of nitroxide radicals in toluene solution than in aqueous solution at low radical concentration. The reason is higher Heisenberg spin exchange rate between different hyperfine EPR transitions due to lower viscosity of toluene. The theoretical model of the relaxation dynamic for the electron-nuclear hyperfine coupled system with S=1/2 and I=1 has been analytically solved and the analytical expressions for the saturation factors of the individual hyperfine lines have been obtained. The electron-electron double resonance (ELDOR) method has been extended for the experimental measurements of the saturation factors and the polarization recoveries for radicals with more than 2 hyperfine lines. The series of experiments have demonstrated that the DNP enhancement increases with increasing of molecular size and does not depend on the nitroxide radical concentration in the case of dominant nitrogen nuclear relaxation between hyperfine EPR transitions. Several nitroxide derivatives with the covalently linked fullerene C60, as the dye with high quantum yield of the triplet state, have been synthetized. The transient EPR experiments of the photoexcited fullerene-nitroxide derivatives have demonstrated the feasibility to generate high non-equilibrium electron spin polarization by light. The photoexcited electron polarization, if successfully transferred to solvent nuclei, may provide a new method to perform DNP in liquids without MW irradiation.
Cross-Scale Haptic Object Recognition for Intelligent Robot

Haptic technology enables robots to touch and understand the interactions between objects in the reality. Advanced haptic sensing systems can not only collect pressure, temperature and stiffness of touched objects, but also avoid destructive operations, and assist in navigation and posture control for robots. In order to smoothly interact with different types of objects, in the haptic system, it is necessary to develop haptic object recognition methods for effective haptic perception capability. However, compared to RGB images, haptic images collected by opticallybased haptic sensors are similar in appearance, which makes traditional convolutional neural networks (e.g.,ResNet, VGG, etc.) ineffective. Therefore, in this paper, we are inspired by popular attention mechanism and multi-scale strategies, and propose a cross-scale attention based haptic object recognition network for object-robot interaction. In particular, On the one hand, we design a cross-scale attention module in convolutional neural networks to acquire spatial contextual feature. On the other hand, we design a learnable bilinear fusion strategy to integrate above spatial contextual feature with original haptic feature, so as to effectively discriminate haptic images. Experimental results on ViTac dataset have shown the effectiveness of our approach.
How Should the Transition from Underwater to Surface Swimming Be Performed by Competitive Swimmers?

Despite the increasing importance of the underwater segment of start and turns in competition and its positive influence on the subsequent surface swimming, there is no evidence on how the transition from underwater to surface swimming should be performed. Therefore, the aim of the present study was to examine the role of segmental, kinematic and coordinative parameters on the swimming velocity during the pre-transition and transition phases. A total of 30 national male swimmers performed 4 × 25 m (one each stroke) from a push start at maximum velocity while recorded from a lateral view by two sequential cameras (50 Hz), and their kinematic and coordinative swimming parameters were calculated by means of two-dimensional direct linear transformation (DLT) algorithms. Unlike pre-transition, backward regression analysis of transition significantly predicted swimming velocity in all strokes except breaststroke (R2 ranging from 0.263 in front crawl to 0.364 in butterfly). The inter-limb coordination was a predictor in butterfly stroke (p = 0.006), whereas the body depth and inclination were predictors in the alternate strokes (front crawl (p = 0.05) and backstroke (p = 0.04)). These results suggest that the body position and coordinative swimming parameters (apart from kicking or stroking rate and length) have an important influence on the transition performance, which depends on the swimming strokes.
Simultaneous Kidney and Liver Resection in Renal Cell Carcinoma Liver Metastases: A Tale of Two Cases

Introduction: Resection of renal cell carcinoma liver metastases (RCCLM) is known to provide a good survival outcome. Simultaneous RCCLM resection with the primary tumor is commonly done in cases with direct extension of locally advanced RCC to liver parenchyma. Cases of safe simultaneous resection of liver and kidney in malignancy have not been reported before in Indonesia. Case Presentation: We aim to describe two cases of left-sided RCC with right-sided RCCLM who underwent simultaneous kidney and liver resection. Both patients had good short-term survival with no intra-operative and post-operative complications. Conclusion: Although simultaneous kidney and liver resection poses challenges of substantial morbidity, a safe surgical and multidisciplinary approach could be implemented in selected cases with a good surgical outcome.
Flexibility oriented HRM practices and innovation: evidence from China and India

Abstract The importance of flexibility as a characteristic of HR systems has been long recognized. Yet, very little work has attempted to conceptualize and measure it for examining desirable outcomes such as innovation. We draw from the theory of dynamic capabilities to develop a testable model. We contribute by theorizing and empirically examining the influence of flexibility-oriented HRM (FHRM) systems on intellectual capital, and by examining the mediating role of intellectual capital in the relationship between FHRM and innovativeness. We test our model using samples from China and India and show support for the hypotheses. Our findings show a specific set of relationships between two FHRM components – Coordination-flexibility-oriented HRM and Resource-flexibility oriented HRM – and the three components of intellectual capital – human, social, and organizational capital. We also find that intellectual capital mediates the relationship between FHRM and firm innovativeness. We discuss findings, limitations, and future directions.
Cyclic Code Word Embedding and Chi-Squared Test-Based Attention Mechanism for Deep Learning-Based Server Fault Detection*

Server log data offers a comprehensive record of system operations, making the analysis of this data via algorithms for autonomous fault diagnosis a critical research area. At present, two primary methods of automatic fault diagnosis prevail: traditional machine learning algorithms, such as random forests, which can efficiently and accurately deliver fault diagnosis results after manual feature extraction; and deep neural network algorithms, which can execute end-to-end fault diagnosis with large data sets and yield superior outcomes compared to the former method. However, both techniques exhibit a significant shortcoming: log files constitute time-series data, but machine learning algorithms struggle to effectively capture sequence information. Conversely, deep learning algorithms based on recurrent neural networks can grasp sequence information but lack a thorough comprehension of the system, rendering their implementation relatively demanding, as it necessitates a considerable volume of labeled data. In this paper, we put forth a groundbreaking solution that amalgamates the strengths of both algorithms. We employ the chi-square test algorithm to extract features via machine learning algorithms and subsequently in-corporate an attention mechanism layer into the neural network. This layer modifies the attention mechanism parameters using the chi-square test output. Moreover, we integrate cyclic codes into the neural network’s word embedding, a technique that has proven highly effective in communication channel coding. We introduce the utilization of Hamming distance to quantify the disparities among various data, thereby facilitating rapid data comprehension by the neural network. Our proposed algorithm has been corroborated using a publicly accessible dataset and demonstrated a 2 percent enhancement in the F1 score.
Fibrinogen and Fibrin Differentially Regulate the Local Hydrodynamic Environment in Neutrophil–Tumor Cell–Endothelial Cell Adhesion System

As cancer is one of the major fatal diseases for human beings worldwide, the metastasis of tumor cells (TCs) from a blood vessel to an adjacent organ has become a focus of research. A tumor metastasis theory named the “two-step theory” pointed out that polymorphnuclear neutrophils (PMNs) could facilitate TC adhesion on an endothelial monolayer under flow, which was regulated by shear flow and promoted by fibrinogen and fibrin. In order to further understand the role of hydrodynamics played in the “two-step theory”, we improved our side-view micro-particle imaging velocimetry (PIV) system and successfully measured the flow velocity profiles around adherent PMNs and TCs on an endothelial monolayer in the presence of soluble fibrinogen or fibrin under shear flow. Combined with a computational fluid dynamics simulation, we found that: (1) soluble fibrinogen and fibrin influenced the variations of relative shear rates above an adhered PMN and an adherent TC at different PMN-to-TC position states; (2) compared with soluble fibrinogen, soluble fibrin made the curves of relative shear rates above an adherent cell flatter. Soluble fibrin might increase the collision frequency and affect the contact time and contact area between PMNs, TCs, and endothelium cells, resulting in the enhancement of TC adhesion and retention on an endothelial monolayer.
Regulatory mechanisms underlying florigenesis in Vanilla planifolia Andrews: A study of MADS-box gene family

ABSTRACT Orchid flowers have unique floral organisation which make them indispensable to the floral industry. The MADS-box gene family encodes for transcription factors that are involved mainly in floral organisation. This study was conducted on Vanilla planifolia, which is an important orchid that is commercially exploited by the food industry for a highly valued flavour, vanillin. V. planifolia transcriptome was analysed and 33 MADS-box transcripts that encode putative MADS-box proteins, were identified. Phylogenetic analysis of the VpMADS proteins with other closely related plant species showed clear clustering into type I and type II. Protein characterisation, duplication events, and their evolutionary analysis were performed. The spatio-temporal expression profile for VpMADS genes at different plant developmental stages showed high expression of these genes in specific floral tissues. Secondary and tertiary structural analyses was also done for 13 MADS-box proteins representing each sub-class and their 3D structures were deduced. This study provides a basic understanding of the functioning of MADS-box gene family in V. planifolia and paves the path for functional characterisation of selected VpMADS genes in planta and in a heterologous system for managing the commercially important traits in this orchid.
Reviewing the Effects of Leader-Member Exchange on Job Crafting via ModeratedMediation Analysis: A Study on Teachers

Design/methodology/approach – The data were collected via questionnaires and simple random sampling while including middle school teachers in a city of Turkey as participants. In addition, data were gathered in October and November 2019. The reason why teachers were selected for this study is the fact that there is limited amount of studies in the literature doing so. In order to test the hypotheses, hierarchical regression analysis, sobel test and moderated mediation analysis were used.
Energy Efficiency in Slew-Rate Enhanced Single-Stage OTAs for Switched-Capacitor Applications

Slew-rate enhancement (SRE) techniques assist the charge transfer process in OTA-based switched-capacitor circuits. Parallel-type slew-rate enhancement circuits, i.e., circuits that provide a feed-forward path external to the main OTA, are attractive solutions, since they introduce a further degree of freedom in the speed/power consumption design space without affecting other specifications regarding the main OTA. This technique lends itself to be employed jointly with advanced OTA topologies in order to compose a highly energy efficient OTA/SRE system. However, insights in design choices such as power optimization are still missing for such systems. Here we discuss system level choices with the help of a simple model. Using precise electrical simulations, we demonstrate energy savings greater than 30% for different OTA/SRE systems implemented in a standard 180-nm CMOS technology.
Spatio-Temporal Change Monitoring of Outside Manure Piles Using Unmanned Aerial Vehicle Images

Water quality deterioration due to outdoor loading of livestock manure requires efficient management of outside manure piles (OMPs). This study was designed to investigate OMPs using unmanned aerial vehicles (UAVs) for efficient management of non-point source pollution in agricultural areas. A UAV was used to acquire image data, and the distribution and cover installation status of OMPs were identified through ortho-images; the volumes of OMP were calculated using digital surface model (DSM). UAV- and terrestrial laser scanning (TLS)-derived DSMs were compared for identifying the accuracy of calculated volumes. The average volume accuracy was 92.45%. From April to October, excluding July, the monthly average volumes of OMPs in the study site ranged from 64.89 m3 to 149.69 m3. Among the 28 OMPs investigated, 18 were located near streams or agricultural waterways. Establishing priority management areas among the OMP sites distributed in a basin is possible using spatial analysis, and it is expected that the application of UAV technology will contribute to the efficient management of OMPs and other non-point source pollutants.
Evidencias de Validez Diagnóstica de la Escala Detectaweb-Malestar

Evidence of diagnostic validity of the DetectaWeb-Distress ScaleAbstract: The DetectaWeb-Distress Scale is a web-based scale for screening and detecting internalizing disorder symptoms (anxiety, depression, posttraumatic stress, obsessions and compulsions, and suicidality) in children and adolescents. Previous studies examined the validity and reliability of the scale, however, there are no data on its diagnostic validity. The objective of this study was to examine the evidence of diagnostic validity of the DetectaWeb-Distress scale in a sample of 244 children and adolescents from clinical (n = 51) and community (n = 193) settings, all of them with the diagnostic process completed. The results indicated that the DetectaWeb-Distress scale is a useful measure from a diagnostic point of view, as it discriminates between people with emotional disorders such as anxiety and depressive disorders and suicidality, and those without, presenting ROC values of approximately . 80 and good sensitivity and specificity for detecting the main emotional disorders. The DetectaWeb-Distress Scale is a valid measure and diagnostically useful for detecting and identifying children and adolescents with anxiety disorders, depression and suicidality, with the advantage that it is a short measure, specifically developed for Internet use, especially relevant in the era of COVID-19.Keywords: DetectaWeb-Distress; assessment, anxiety, depression, children, adolescents.Evidencias de Validez Diagnóstica de la Escala Detectaweb-Malestar Resumen: La Escala DetectaWeb-Malestar es una escala de detección del malestar emocional a través de internet que evalúa síntomas de trastornos interiorizados (ansiedad, depresión, estrés postraumático, obsesiones y compulsiones y suicidalidad) en niños y adolescentes. Estudios anteriores han examinado la validez y fiabilidad de la escala, sin embargo, no cuenta con datos relativos a su validez diagnóstica. El objetivo de este estudio es examinar las evidencias de validez diagnóstica de la escala DetectaWeb-Malestar en una muestra de 244 niños y adolescentes procedentes de contextos clínico (n = 51) y comunitario (n = 193), todos con un proceso diagnóstico completado. Los resultados indicaron que la escala DetectaWeb-Malestar es una medida útil desde el punto de vista diagnóstico, ya que discrimina entre personas con trastornos de emocionales, como son los de ansiedad, depresión y suicidalidad y los que no lo padecen, presentando valores ROC en torno a . 80 y adecuada sensibilidad y especificidad para detectar los principales trastornos emocionales. La escala DetectaWeb-Malestar es una medida válida y útil desde el punto de vista diagnóstico para detectar e identificar niños y adolescentes con problemas de ansiedad, depresión y suicidalidad, con la ventaja de que es una medida breve y desarrollada específicamente para su uso a través de Internet, especialmente relevante en la era de la COVID-19.Palabras clave: DetectaWeb-Malestar; evaluación; ansiedad; depresión; niños y adolescentes.