Miracle-dz/UniFAR-FTUs huggingface dataset:
DIGITAL BASED CAPABILITIES IN LIFE INSURANCE COMPANIES: AN EXPLORATORY STUDY IN INDONESIA

Asuransi jiwa penting karena menawarkan perlindungan untuk mengurangi risiko bagi pemegang polis. Industri asuransi jiwa di Indonesia memiliki kontribusi yang signifikan dalam industri keuangan Indonesia meskipun mengalami fenomena tingkat penetrasi yang rendah, literasi yang buruk, perlindungan konsumen dan praktik misselling. Kajian ini menggunakan pendekatan studi kasus melalui serangkaian wawancara mendalam pada beberapa perusahaan asuransi jiwa dengan mengeksplorasi pengamalam transformasi digital mereka. Kajian ini mengeksplorasi kondisi eksisting perusahaan asuransi jiwa Indonesia dalam mengembangkan kapabilitas dinamis berbasis digital serta kapabilitas transformasional penyediaan layanan dalam menciptakan SCA digital untuk bertahan di industri asuransi jiwa Indonesia. Studi ini mengidentifikasi dan membahas tiga tema utama yang terdiri dari pengembangan perjalanan pelanggan yang tepat, mendapatkan kepercayaan, dan tantangan utama sebagai faktor kunci keberhasilan dalam mengembangkan dan menggunakan kemampuan tersebut. Penelitian ini menghasilkan tiga proposisi dan menyarankan studi eksplanatori lebih lanjut untuk mengkaji proposisi-proposisi tersebut. Life insurance is important as it offers protection to mitigate risks for the policyholders. Life insurance industry in Indonesia has a significant contribution in Indonesia financial industry although it experiences phenomena of low penetration rate, poor literacy, consumer protection and misselling practices. This study used case study approach through series of deep dive interviews with selected life insurance companies exploring their digital transformation experiences. This study explored the existing conditions of Indonesia lifeinsurance companies in developing their digital based dynamic capabilities as well as the service provisioning transformational capability in creating the digital SCA to survive in Indonesia life insurance industry. This study identified and discussed three key themes consisted of development of the right customer journey, earn trust, and key challenges as key success factor in developing and exercising the said capabilities. The study resulted in three propositions and suggested further explanatory study to examine the propositions.
PACE-IT: designing blended learning for accounting education in the challenging context of a global pandemic

ABSTRACT This paper describes the design of a blended learning intervention to enhance the student learning experience, incorporating innovative technologies and pedagogies within introductory accounting. The design-based research (DBR) methodology involved 68 learners in the participatory design of the intervention across three design iterations. Emerging from the design process, a framework informed by the key themes of Pedagogy, Autonomy, Collaboration, Engagement, Interaction and Technology (PACE-IT) was conceptualised, tested and developed. This study presents the PACE-IT model which offers guidelines to practitioners who seek to design blended learning to provide students with a rich and meaningful learning experience. The emergence of COVID-19 underscores the relevance of these findings. PACE-IT provides direction to accounting educators working within an unfamiliar educational context, today and in the future, where there is an imperative to develop new approaches to accounting education that combine face-to-face with online interaction and learning.
An elastic plate on a thin viscous film

We consider the steady-state analysis of a pinned elastic plate lying on the free surface of a thin viscous fluid, forced by the motion of a bottom substrate moving at constant speed. A mathematical model incorporating elasticity, viscosity, surface tension, and pressure forces is derived, and consists of a third-order Landau-Levich equation for the thin film, and a fifth-order beam equation for the plate. A numerical and asymptotic analysis is presented in the relevant limits of the elasticity and Capillary numbers. We demonstrate the emergence of boundary-layer effects near the ends of the plate, which are likely to be a generic phenomenon for singularly perturbed elastocapillary problems.
Infrared Dim Small Target Tracking Based on Inter-frame Consistency Under Complex Background

Based on the inter-frame correlation and continuity of target features, a method of dim small target tracking in the infrared sequence is proposed. To depress the noise, the spatial hard constraint is used to eliminate the noise that is far away from the target, and the credibility soft constraint evaluates the indistinguishable noise that is close and similar to the target. Aiming at the disappearance of the target caused by the over-bright region, the prior information of the target trajectory of known frames in the past is fully excavated to improve the continuity of target tracking. All the above contributions have been integrated into a unified framework, which is a probabilistic pipeline filtering algorithm with trajectory prediction. The experimental results on five different infrared image sequences prove that the proposed algorithm can effectively improve the robustness and accuracy of tracking in complex environments.
Mobile tablets for real-time data collection for hospital-based birth defects surveillance in Kampala, Uganda: Lessons learned

Sustainable birth defects surveillance systems provide countries with estimates of the prevalence of birth defects to guide prevention, care activities, and evaluate interventions. We used free and open-source software (Open Data Kit) to implement an electronic system to collect data for a hospital-based birth defects surveillance system at four major hospitals in Kampala, Uganda. We describe the establishment, successes, challenges, and lessons learned from using mobile tablets to capture data and photographs. After intensive training, surveillance midwives collected data using Android tablets with inbuilt logic checks; another surveillance midwife checked the quality of the data in real-time before data were securely uploaded onto a local server. Paper forms were used when needed as a backup for the electronic system. We experienced several challenges implementing the surveillance system, including forgotten passwords, unstable network, reduced tablet speed and freezing, loss of touch-screen sensitivity, decreased battery strength, and repetitive extensive retraining. We addressed these challenges by backing up and removing all photos from the tablet, uninstalling irrelevant applications to the study to increase storage space and speed, and monitoring and updating the system based mainly on feedback from the midwives. From August 2015 to December 2018, surveillance midwives documented information on 110,752 births at the participating hospitals. Of these, 110,573 (99.8%) were directly entered into the electronic data system and 179 (0.2%) were captured on paper forms. The use of mobile tablets for real-time data collection was successful in a hospital-based birth defects surveillance system in a resource-limited setting. Extensive training and follow-up can overcome challenges and are key to preparing staff for a successful data collection system.
Testing System Development for Full-Scale Simulators of Nuclear Power Plant Unit

The full-scale simulator (FSS) of nuclear power plant (NPP) unit is designed for operating personnel professional joint training of the power unit’s main control room using its real full-scale model. Testing of all FSS systems has an important place in the software part of the development of FSS. Currently, the development of software testing for FSS systems is required. The article provides an overview ozf modern testing systems. In addition, the article presents the algorithms for the operation of tests designed by using Pytest – the framework for writing software tests. The paper presents the following tests: overpower test and check for the presence of chugging; test of the correctness of the decay heat model in terms of amplitude in the event of scram and stable attenuation of decay heat after scram.
Optimal Sector-Based Sequential Model Predictive Control for Current Source Rectifier

Conventional model predictive control (MPC) methods for current source rectifier (CSR) use either a PI controller or weight factor-based methods, which require time-consuming tuning methods to develop an efficient controller. Moreover, the limitations on the bandwidth requirements of the $LC$ filter cause resonances and grid current distortions if a variable switching frequency-based predictive control is used. So, a new fixed switching frequency-based MPC algorithm has been developed to control the load and source current simultaneously, thereby facilitating the weight factor less operation and applying a predefined space vector sequence. Unlike the conventional single cost function methods applied to CSR, the proposed method uses separate cost function for each control variable. Simultaneously, to provide fixed frequency operation, duty ratio-based modulation of grid current control has been applied. A virtual impedance-based active damping has been embedded into the supply current control to suppress the oscillations caused by the $LC$ filter and grid current harmonics. Simulation and experimental results have been supported to validate the improvements in terms of supply current total harmonic distortion (THD), steady state, and transient switching performance.
Erythropoietin Enhances Post-ischemic Migration and Phagocytosis and Alleviates the Activation of Inflammasomes in Human Microglial Cells

Recombinant human erythropoietin (rhEPO) has been shown to exert anti-apoptotic and anti-inflammatory effects after cerebral ischemia. Inflammatory cytokines interleukin-1β and -18 (IL-1β and IL-18) are crucial mediators of apoptosis and are maturated by multiprotein complexes termed inflammasomes. Microglia are the first responders to post-ischemic brain damage and are a main source of inflammasomes. However, the impact of rhEPO on microglial activation and the subsequent induction of inflammasomes after ischemia remains elusive. To address this, we subjected human microglial clone 3 (HMC-3) cells to various durations of oxygen-glucose-deprivation/reperfusion (OGD/R) to assess the impact of rhEPO on cell viability, metabolic activity, oxidative stress, phagocytosis, migration, as well as on the regulation and activation of the NLRP1, NLRP3, NLRC4, and AIM2 inflammasomes. Administration of rhEPO mitigated OGD/R-induced oxidative stress and cell death. Additionally, it enhanced metabolic activity, migration and phagocytosis of HMC-3. Moreover, rhEPO attenuated post-ischemic activation and regulation of the NLRP1, NLRP3, NLRC4, and AIM2 inflammasomes as well as their downstream effectors CASPASE1 and IL-1β. Pharmacological inhibition of NLRP3 via MCC950 had no effect on the activation of CASPASE1 and maturation of IL-1β after OGD/R, but increased protein levels of NLRP1, NLRC4, and AIM2, suggesting compensatory activities among inflammasomes. We provide evidence that EPO-conveyed anti-inflammatory actions might be mediated via the regulation of the inflammasomes.
SAR Ship Detection Based on Enhanced Attention Mechanism

Deep learning has made great achievements in synthetic aperture radar (SAR) target detection. However, due to the complex imaging mechanism, SAR ship targets are generally small, which brings huge difficulties to SAR target detection. To alleviate this problem, we integrate an enhanced attention module (EAM) based on the convolutional block attention module (CBAM) into Cascade RCNN. EAM is used to enhance SAR ship scattering information and suppress invalid features. EAM consists of modified channel attention for channel features fusion and modified spatial attention to focus on significant information. Finally, experiments on the SAR ship detection dataset (SSDD) and Hisea-1 system ship data demonstrate that the proposed method achieves better detection performance.
Long-term trends of second generation anticoagulant rodenticides (SGARs) show widespread contamination of a bird-eating predator, the Eurasian Sparrowhawk (Accipiter nisus) in Britain.

Second generation anticoagulant rodenticides (SGARs) are widely used to control rodents around the world. However, contamination by SGARs is detectable in many non-target species, particularly carnivorous mammals or birds-of-prey that hunt or scavenge on poisoned rodents. The SGAR trophic transfer pathway via rodents and their predators/scavengers appears widespread, but little is known of other pathways of SGAR contamination in non-target wildlife. This is despite the detection of SGARs in predators that do not eat rodents, such as specialist bird-eating hawks. We used a Bayesian modelling framework to examine the extent and spatio-temporal trends of SGAR contamination in the livers of 259 Eurasian Sparrowhawks, a specialist bird-eating raptor, in regions of Britain during 1995-2015. SGARs, predominantly difenacoum, were detected in 81% of birds, with highest concentrations in males and adults. SGAR concentrations in birds were lowest in Scotland and higher or increasing in other regions of Britain, which had a greater arable or urban land cover where SGARs may be widely deployed for rodent control. However, there was no overall trend for Britain, and 97% of SGAR residues in Eurasian Sparrowhawks were below 100 ng/g (wet weight), which is a potential threshold for lethal effects. The results have potential implications for the population decline of Eurasian Sparrowhawks in Britain. Fundamentally, the results indicate an extensive and persistent contamination of the avian trophic transfer pathway on a national scale, where bird-eating raptors and, by extension, their prey appear to be widely exposed to SGARs. Consequently, these findings have implications for wildlife contamination worldwide, wherever these common rodenticides are deployed, as widespread exposure of non-target species can apparently occur via multiple trophic transfer pathways involving birds as well as rodents.
ON LOCAL AND GLOBAL ASPECTS OF THE CAUCHY PROBLEM IN GENERAL RELATIVITY

In this paper we review some of the recent mathematical progress concerning the initial value problem formulation of general relativity. It is not our intention, however, to give an exhaustive presentation of all recent results on this topic, but rather to discuss some of the most promising mathematical techniques, which have been advanced in connection with the general Cauchy problem, in the absence of any special symmetries. Moreover, for the sake of simplicity and coherence, we restrict ourselves to the Einstein vacuum equations in the asymptotically flat regime. Our main goal is to discuss the main mathematical methods behind the various local existence and uniqueness results, as well as those used in the proof of global nonlinear stability of the Minkowski space. We also present an outline of a somewhat different and more transparent approach obtained by the authors in collaboration with Christodoulou. This relies, instead of the maximal foliation used by Christodoulou and Klainerman, on a double-null foliation. The new approach is fully adapted to domains of dependence and thus allows one to provide, directly, without having to rely on interior estimates, a proof of stability of `null infinity' for large asymptotically flat initial data sets.
Distributed Constrained Online Convex Optimization Over Multiple Access Fading Channels

In this paper, we study distributed constrained online convex optimization for a wireless system consisting of a parameter server and multiple agents. Each agent has a local constraint function and a time-varying local loss function, and needs to choose sequential actions based on causal information. The goal of the overall system is to minimize the accumulated total loss of all agents over a time horizon subject to total constraints of the agents. To this end, the agents communicate with the server over multiple access noisy fading channels, where the information is exchanged imperfectly. We first consider the full information scenario, where the local loss function of each agent is fully revealed to the corresponding agent in each time slot. We propose a modified saddle-point algorithm, where each agent sends an analog signal pertaining to the current value of the local constraint function and the server receives a superposition of these signals distorted by the noisy fading channels. We analyze the performance of the proposed algorithm, and establish <inline-formula><tex-math notation="LaTeX">$\mathcal {O}(\sqrt{T})$</tex-math></inline-formula> regret bound and <inline-formula><tex-math notation="LaTeX">$\mathcal {O}(T^\frac{3}{4})$</tex-math></inline-formula> constraint violation bound for the algorithm, where <inline-formula><tex-math notation="LaTeX">$T$</tex-math></inline-formula> is the time horizon. Further, we extend the algorithm and performance analyses to the scenario of bandit feedback, where only the values of the local loss functions at two random points are disclosed to the agents in every time slot. In such a case, performance bounds similar to the full information scenario are established. Finally, numerical examples are presented to corroborate the efficacy of the proposed algorithms.
Design of high‐efficiency CMOS rectifier with low reverse leakage for RF energy harvesting

A CMOS cross-coupled RF rectifier that improves power conversion efficiency (PCE) with low reverse leakage current for energy harvesting wireless sensors is proposed. In this Letter, the authors propose a CMOS cross-coupled differential RF rectifier that uses a thick-oxide MOSFET as a rectifying device to improve PCE by reducing reverse leakage current. The proposed rectifier is designed for UHF band application using 0.18 µm CMOS technology. Proposed rectifier achieves a peak PCE of 75.2% and sensitivity of − 17 dBm for 1 V output voltage. Peak PCE is improved by 8.8% compared to the conventional rectifier.
Self-Supervised Learning of Visual Servoing for Low-Rigidity Robots Considering Temporal Body Changes

In this study, we investigate object grasping by visual servoing in a low-rigidity robot. It is difficult for a low-rigidity robot to handle its own body as intended compared to a rigid robot, and calibration between vision and body takes some time. In addition, the robot must constantly adapt to changes in its body, such as the change in camera position and change in joints due to aging. Therefore, we develop a method for a low-rigidity robot to autonomously learn visual servoing of its body. We also develop a mechanism that can adaptively change its visual servoing according to temporal body changes. We apply our method to a low-rigidity 6-axis arm, MyCobot, and confirm its effectiveness by conducting object grasping experiments based on visual servoing.
Modelling mobile robot navigation in 3D environments: camera-based stairs recognition in Gazebo

The task of sensory-based autonomous navigation of mobile robots requires data fusion from multiple sources in order to properly detect and recognize environmental obstacles. One of important issues mobile robots deal in a typical multi-level indoor environment is a stair well detection and negotiation. This paper presents ROS-based stairs detection implementation using onboard cameras of the Russian mobile crawler robot Servosila Engineer. Virtual experiments were performed in Gazebo environment with a single camera and a stereo camera.
Triple droop control method for ac microgrids

In this study, a novel droop control method for ac microgrids is proposed to enhance the performance of power regulation, which is composed of three parts. The angle droop and the frequency droop are adopted to control the active power in coordination, while the modified voltage droop is used to control the reactive power. There are several improvements in this proposed triple droop control method compared with the conventional droop control. First, the dynamics of active power regulation are enhanced because of the angle droop. Second, the stability of the system is upgraded and the droop coefficients can vary in greater range. Third, the accuracy of reactive power regulation is improved, especially in the grid-connected mode, the DGs can output the specified reactive power with the modified voltage droop, which benefits the economic dispatch of the microgrid. Through these three combined droop control strategies, the performance of the whole system can be improved a lot whether in the grid-connected mode or the islanded mode. Furthermore, the stability of the proposed triple droop control is analysed, which shows that the stability of the system is upgraded. The effectiveness of the proposed control method is verified by the hardware-in-loop tests.
The Inflammatory Factor SNP May Serve as a Promising Biomarker for Acitretin to Alleviate Secondary Failure of Response to TNF-a Monoclonal Antibodies in Psoriasis

Psoriasis is a common immune-mediated inflammatory skin disease. Although biological agents have achieved good clinical efficacy in the treatment of moderate-to-severe psoriasis, the phenomenon of secondary non-response (SNR) has been gradually recognized. SNR refers to the gradual decline of efficacy after the patient achieves clinical remission with biological agents such as TNF-α biologics. Acitretin, as an immunomodulatory systemic drug for psoriasis, can improve the SNR to biological agents with good tolerance, but there are still individual differences in efficacy. Single-nucleotide polymorphisms (SNPs) of many related inflammatory cytokines have been shown to be important factors of individual differences in drug response in psoriasis, but there have been few reports on the use of pharmacogenomics to alleviate the SNR to biological agents. This study recruited 43 patients with psoriasis and 24 normal controls to investigate whether SNPs of inflammatory cytokines could be used as biomarkers for acitretin to alleviate SNR to TNF-α biologics in psoriasis, including rs1800795 (IL-6), rs6887695 (IL-12b), rs3212227 (IL-12b), rs10484879 (IL-17a), rs4819554 (IL-17ra), rs763780 (IL-17F), rs11209032 (IL23R), rs11209026 (IL23R), and rs2201841 (IL23R). The study also analyzed the correlation between the abovementioned SNPs and the efficacy of acitretin-only patients so as to understand whether the improvement is attributable to the intervention of acitretin on SNR or a simple response of acitretin. We found that in patients with homozygous AA (χ2 = 6.577, p = 0.02) at the SNP rs112009032 (IL-23R), acitretin could improve the SNR to TNFα monoclonal antibody. Patients with the genotype of TG (χ2 = 6.124, p = 0.035) at rs3212227 (IL-12B) were more sensitive to using acitretin in the treatment of psoriasis. Rs3212227 (χ2 = 7.664, p = 0.022) was also associated with the susceptibility to psoriasis. The study might provide a clinical decision reference for personalized treatment of secondary loss of response to psoriasis biologics.