Long-term Product Research Articles

Radar versus optical: The impact of cloud cover when mapping seasonal surface water for health applications in monsoon-affected India.

Surface water plays a vital role in the spread of infectious diseases. Information on the spatial and temporal dynamics of surface water availability is thus critical to understanding, monitoring and forecasting disease outbreaks. Before the launch of Sentinel-1 Synthetic Aperture Radar (SAR) missions, surface water availability has been captured at various spatial scales through approaches based on optical remote sensing data. A critical drawback of the latter is data loss due to cloud cover, however few studies have quantified this. This study evaluated data loss due to clouds in three Western Ghats (India) districts. These forest-agricultural mosaic landscapes, where water-related diseases are prevalent, experience the Indian monsoon. We compared surface water areas mapped by thresholding 10m Sentinel-1A SAR data with the optical 30m Landsat-derived Joint Research Centre (JRC) Global Surface Water product, currently the only globally available long-term monthly surface water data product. Backscatter thresholds were identified manually, and our Bayesian algorithm found these thresholds were very likely (>97%). While the Sentinel-1 SAR-based and JRC's optical-based approach mapped surface water extent with high overall accuracy (> 98%) when the cloud cover was low, the unmapped surface water area was substantial in the JRC product during the monsoon months. Across the districts, the average cloud cover in the July-August period was 92% or 90% for 2017 and 2018 respectively, resulting in 25% or 23% of the surface water area being unmapped. Also, the more detailed 10m resolution of Sentinel-1A SAR helped detect the many small water features missed by 30m JRC. Thus, for predicting water-related disease risks linked to small water features or monsoon rainfall, Sentinel-1A SAR is more effective. Finally, automatic backscatter thresholding for unvegetated surface water mapping can be effective if threshold values are adapted to regional-specific backscatter spatial and temporal variations.

Long-Term Savings as a Source of Oil Palm Replanting Financing

Replanting activities are one of the ways to maintain the productivity of oil palm plants. The large costs required in replanting indicate that financial planning is needed to ensure the implementation of replanting can be realized properly. This study aims to calculate the value of savings to prepare for the needs of oil palm replanting funds and provide recommendations for the implementation plan of long-term savings activities that can be carried out by oil palm farmers. This research method uses a quantitative-qualitative method. The key informants in this study were officers at KPKS Suka Makmur and employees at Bank Sumsel Babel. The informants were selected by purposive sampling by considering their expertise in oil palm replanting activities and long-term savings products. Based on the results of the research, it is known that the value of savings that must be prepared by farmers in one month is IDR 294,256.54 per hectare. Farmers can save their savings in two schemes, which are using an institutional account or a personal account. It is expected that farmers can prepare replanting funds through regular monthly savings through long-term savings in the name of an institution or group. In addition, there is a need for socialization and discussion by cooperatives or farmer groups to their members regarding the future financial plans of oil palm farming so that farmers can properly prepare for the needs of oil palm replanting funds

Infrared treatment influence on the buckwheat groats structural and mechanical properties

One of the most popular grain crops is buckwheat. Buckwheat and its processed products have high digestibility, high nutritional value and low glycemic index, which is beneficial for people with diabetes mellitus types I and II. Buckwheat groats – a processed buckwheat product – are the second most popular on the market after rice. Based on the results of the studies, a technology for infrared processing of buckwheat has been developed. The presence of two areas of infrared radiation impact on buckwheat has been confirmed: the area of thermal destruction (steam formation) and the area of drying, when the water inside the product diffuses to the surface in the form of liquid and evaporates from the surface. The optimal parameters for intensive infrared processing of buckwheat have been established: radiant flux power of 32–34 kW/m², humidity of 14%, temperature of 135–140 °C; processing time of 35–40 s. It was found that the radiant flux density during IR treatment should not exceed 35 kW/m² to avoid burning of the cereal surface and deterioration of consumer qualities. It was found that the bulk density of buckwheat during IR treatment decreases by 1.6 times compared to untreated cereals. It was found that during infrared heat treatment of buckwheat, moisture evaporates, and its humidity decreases to 7.5–8.0%, which allows classifying it as a long-term storage product. It was found that during infrared treatment according to the developed method, the amount of extractive substances in buckwheat groats increases by 4 times.

Molecular complex inspired design of an efficient copper(II)-containing robust porous polymers for electrochemical water oxidation

Homogeneous copper-bipyridine complexes have been reported as effective catalysts for water oxidation, demonstrating significant potential as alternatives to precious metal-based complexes. However, these complexes face long-term stability and product separation challenges similar to many homogeneous catalysts. Meanwhile, recent studies have underscored the potential of metalated polymer networks, which integrate the structural advantages of polymers with the functional benefits of metal species, making them highly attractive for various applications. Herein, we integrated copper-bipyridine units into porous polymer networks to overcome the limitations of copper-bipyridine complexes. We prepared a series of copper-incorporated polymers (TpBpy-Cux) for electrochemical water oxidation. The electrochemical properties of these polymers were tuned by varying the copper content, with TpBpy-Cu3 presenting the best performance among the samples studied. TpBpy-Cu3 demonstrated a low Tafel slope of 69 mV/decade, achieved a high Faradaic efficiency (FE) of 94 %, and exhibited exceptional stability over 1000 cyclic scans. This study offers insights into the design and optimization of metal-incorporated porous polymer networks building on the foundational understanding of their molecular counterparts for advanced catalytic applications.

Influence of Terrain on MODIS and GLASS Leaf Area Index (LAI) Products in Qinling Mountains Forests

Leaf Area Index (LAI), as a pivotal parameter in characterizing the structural properties of vegetation ecosystems, holds significant importance in assessing the carbon sink function. Given the availability of multiple long-term LAI products, validating these LAI products with consideration of topographic factors is a prerequisite for enhancing the quality of LAI products in mountainous areas. Therefore, this study aims to evaluate the performance of MODIS LAI and GLASS LAI products from 2001 to 2021 by comparing and validating them with ground-measured LAI data, focusing on the spatio-temporal and topographic aspects in the Qinling Mountains. The results show that the GLASS LAI product is a better choice for estimating LAI in the Qinling Mountains. The GLASS LAI product has better completeness and generally higher values compared to the MODIS LAI product. The time-series curve of the GLASS LAI product is more continuous and smoother than the MODIS LAI product. Both products, however, face challenges in quantifying LAI values of evergreen vegetation during winter. The MODIS and GLASS LAI products exhibit differences between sunny and shady slopes, with mean LAI values peaking on sunny slopes and reaching their lowest on shady slopes. When the slope ranges from 0 to 10°, the mean values of GLASS LAI product show a higher increasing trend compared to the MODIS LAI product. At elevations between 1450 and 2450 m, the mean LAI values of the GLASS LAI product are higher than the MODIS LAI product, primarily in the southern Qinling Mountains. Compared to ground-measured LAI data, the GLASS LAI product (R² = 0.33, RMSE = 1.62, MAE = 0.61) shows a stronger correlation and higher accuracy than the MODIS LAI product (R² = 0.24, RMSE = 1.61, MAE = 0.68).

Physicochemical Attributes Related to Sensory Characteristics of Long-Term Aged Korean Traditional Soy Sauce (Ganjang).

This study investigated the physicochemical properties influencing the sensory characteristics of long-term aged ganjang. Eight ganjang samples aged 3, 10, and 15 years were obtained from three different manufacturers and analyzed for physicochemical characteristics, sensory profiles, and consumer acceptability. The proximate composition (moisture, ash, protein, and crude fat), total solids, salinity, acidity, pH, color (L, a, b, chrome, and hue), 27 free amino acids (FAAs), and volatile compounds were analyzed. Quantitative descriptive analysis was performed by 11 trained panelists for sensory profiles and 102 consumers evaluated consumer acceptability (overall, appearance, odor, taste/flavor, and mouthfeel). The results demonstrated a positive correlation between the aging period and increases in total solids, proteins, crude fat, acidity, color hue, FAA, major volatile compounds, and overall consumer acceptability. Specifically, correlation maps by partial least squares regression between descriptive attributes and FAAs or volatile compounds revealed that these components significantly affected consumer acceptability. Furthermore, sensory attributes such as color intensity, viscosity, sweetness, umami, and aftertaste were positively correlated with consumer preference, whereas attributes such as greenish-brown color, fish sauce-like flavor, and moldy notes were negatively correlated. Overall, these findings could be utilized to enhance the marketability and consumer appeal of long-term aged ganjang products by providing objective information supporting premium values.

Generating Long-term GRACE-like Total Water Storage Change Products using Conditional Generative Adversarial Networks

Abstract. Since 2002, the Gravity Recovery And Climate Experiment (GRACE) and its Follow-On (GRACE-FO, hereafter GRACE) missions have offered global observations of total water storage (TWS). However, the relatively short record of GRACE data poses a significant challenge for researchers to investigate the full range and long-term variability in TWS. In this study, we present RecGAN, a novel Conditional Generative Adversarial Network (CGAN) comprising a RecNet generator and pixel discriminator. Our approach aims to generate long-term GRACE-like TWS observations by calibrating the WaterGAP Global Hydrology Model (WGHM). The generator is trained to produce observations conforming to the distribution of GRACE data, while the discriminator is trained to assess whether each generated pixel resembles GRACE data. Our results show that RecGAN effectively enhances the consistency between GRACE observations and WGHM-derived TWS changes, achieving improved correlation coefficients, Nash-Sutcliffe Efficiency, and Normalized Root-Mean-Square Error. In addition, RecGAN is robust to different GRACE mascon data, crop sizes used during the training period, and hydrological models targeted for calibration. This study illustrates a promising application of employing CGANs to fine-tune the WGHM output to match GRACE observations. This approach enables the generation of longterm TWS change datasets, which are invaluable for evaluating long-term water storage fluctuations, allocating water resources, and forecasting future hydrological extremes.

Estimating Vertical Distribution of Total Suspended Matter in Coastal Waters Using Remote-Sensing Approaches

The vertical distribution of the marine total suspended matter (TSM) concentration significantly influences marine material transport, sedimentation processes, and biogeochemical cycles. Traditional field observations are constrained by limited spatial and temporal coverage, necessitating the use of remote-sensing technology to comprehensively understand TSM variations over extensive areas and periods. This study proposes a remote-sensing approach to estimate the vertical distribution of TSM concentrations using MODIS satellite data, with the Bohai Sea and Yellow Sea (BSYS) as a case study. Extensive field measurements across various hydrological conditions and seasons enabled accurate reconstruction of in situ TSM vertical distributions from bio-optical parameters, including the attenuation coefficient, particle backscattering coefficient, particle size, and number concentration, achieving a determination coefficient of 0.90 and a mean absolute percentage error of 26.5%. In situ measurements revealed two distinct TSM vertical profile types (vertically uniform and increasing) and significant variation in TSM profiles in the BSYS. Using surface TSM concentrations, wind speed, and water depth, we developed and validated a remote-sensing approach to classify TSM vertical profile types, achieving an accuracy of 84.3%. Combining this classification with a layer-to-layer regression model, we successfully estimated TSM vertical profiles from MODIS observation. Long-term MODIS product analysis revealed significant spatiotemporal variations in TSM vertical distributions and column-integrated TSM concentrations, particularly in nearshore regions. These findings provide valuable insights for studying marine sedimentation and biological processes and offer a reference for the remote-sensing estimation of the TSM vertical distribution in other marine regions.

Aerosol Components Derived from Global AERONET Measurements by GRASP: A New Value-Added Aerosol Component Global Dataset and Its Application

Abstract Aerosols affect Earth’s climate both directly and indirectly, which is the largest uncertainty in the assessment of radiative forcings affecting anthropogenic climate change. The standard Aerosol Robotic Network (AERONET) aerosol products have been widely used for more than 30 years. Currently, there is strong community interest in the possibility of determining aerosol composition directly from remote sensing observations. This work presents the results of applying such a recently developed approach by Li et al. to extended datasets of the directional sky radiances and spectral aerosol optical depth (AOD) measured by AERONET for the retrievals of aerosol components. First, the validation of aerosol optical properties retrieved by this component approach with AERONET standard products shows good agreement. Then, spatiotemporal variations of the obtained aerosol component concentration are characterized globally, especially the absorbing aerosol species (black carbon, brown carbon, and iron oxides) and scattering aerosol species (organic carbon, quartz, and inorganic salts). Finally, we compared the black carbon (BC) and dust column concentration retrievals to the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), products in several regions of interest (Amazon zone, Indo-China Peninsula, North India, southern Africa, sub-Sahel, Gobi Desert, Middle East, Sahara Desert, and Taklamakan Desert) for new insights on the quantitative assessment of MERRA-2 aerosol composition products (R = 0.60–0.85 for BC; R = 0.75–0.90 for dust). The new value-added and long-term aerosol composition product globally is available online (https://doi.org/10.6084/m9.figshare.25415239.v1), which provides important measurements for the improvement and optimization of aerosol modeling to enhance estimation of the aerosol radiative forcing.

Mesoscopic simulation of concrete drying shrinkage with hydration kinetics

Shrinkage-induced cracking significantly impacts the durability of mass concrete structures. Quantitatively evaluating drying shrinkage of concrete proves challenging due to the time-consuming experiments and overlooked microstructure changes during the hydration process. To address this concern, this study initially characterized the long-term hydration products and microstructure of low-heat Portland cement (LHPC) through microstructural experiments. Subsequently, a novel high-resolution mesoscale framework is developed to investigate the drying shrinkage with hydration kinetics. High-resolution models consist of realistic-shaped aggregates are validated by the aggregate morphology and gradation parameters of core sample from mass concrete. Concurrently, the quantitative effects of internal and external factors on LHPC drying shrinkage are explored. Results indicated that LHPC possesses a denser microstructure, lower porosity, higher carbonation resistance, and 20% lower drying shrinkage compared to moderate-heat Portland cement, suggesting promising applications. Furthermore, experimental and computational findings suggested that increasing aggregate volume, controlling aggregate morphology, and adjusting curing time and humidity could be employed to reduce and manage drying shrinkage, ensuring concrete structure durability.

The Effect of the RMAT Designation on Biotechnology Stock Prices, Drug Development Timelines and Outcomes: An Empirical Analysis

This research examines the impact of the U.S. FDA's Regenerative Medicine Advanced Therapy (RMAT) designation on biotechnology and small pharmaceutical companies, focusing on both stock price reactions and drug development timelines. The research employs an event-study methodology to analyze share price movements following RMAT announcements and evaluates the long-term product development outcomes for these companies. Findings reveal that while RMAT designation leads to an initial short-term stock price increase of approximately 8.11% within five days, this optimism diminishes over time, with long-term trends showing a decline in stock value. Furthermore, products under RMAT designation exhibited longer development timelines compared to non-RMAT therapies, raising questions about the designation's effectiveness in accelerating product availability. The study underscores the complex implications of RMAT for stakeholders, emphasizing the need for strategic planning and further regulatory refinement to better align short-term investor expectations with long-term product development realities.

Implementasi Metode New Jersey dalam Perhitungan Cadangan Premi dengan Suku Bunga Stokastik dan Konstan

Premium reserve allocation represents an obligation undertaken by insurance companies to set aside funds for future claims payment to policyholders. Some insurance companies have faced operational challenges, leading to their closure, primarily due to inaccurate premium reserve computations. This research aims to calculate premium reserve in lifelong insurance using the New Jersey method, an improvement upon the Illionis method. The New Jersey method initiates the premium reserve at the beginning or end of the first year at zero dollars. The majority of premium reserve calculations still rely on constant interest rates. However, in reality, this approach inadequately reflects future fluctuations in interest rates, which are crucial for long-term life insurance products. Therefore, this study implements a more realistic approach using stochastic elements, using the Vasicek stochastic interest rate model to determine premium reserve values. From this research, it was found that there was quite a significant difference between the New Jersey method premium reserve value and the two interest rates. The calculation graph shows that the premium reserve value using the Vasicek model of stochastic interest rates tends to be lower than when using constant interest rates. This can be caused by the results of non-constan variations in interest rates in the Vasicek model which ultimately results in fluctuations in interest rates which wffect the calculation of premium reserve.

Using Version Control Information to Visualize Developers' Knowledge

It is not always clear in case of a software project who has the right amount of knowledge concerning a certain module or file. Programmers frequently ask questions like "Who knows the most about this code?" or "Who can I ask for help when I work on this module?". In a large, long-term software product, knowledge is distributed in an uneven way among developers. Developer fluctuation during the product lifetime might cause some parts of the code to be known very well by a multitude of developers, while other parts might sink to the "gray zone", where developer competence is dangerously scarce. It is important for the project management to identify such critical points, to avoid the complete loss of competence. Version control repositories contain loads of useful information about the evolution of a software project. This paper presents a developer-centered visualization that is intended to show individual, team-bound and company-bound knowledge of large legacy projects. The competence information is computed from the extracted version control information from Git repositories. The calculated competence value is based on the number of commits per developer and their significance. Aggregated views for teams and companies are available based on various heuristics. The visualization is implemented as a new plugin in CodeCompass, a standalone, open-source code comprehension software. Project managers and individual developers may both profit from the tool, whether it concerns software evolution, human-resource management, architecture, knowledge catch-up, or blame.

Evaluation and analysis of long-term MODIS MAIAC aerosol products in China

NASA has released the latest Moderate Resolution Imaging Spectroradiometer (MODIS) Multi-Angle Implementation of Atmospheric Correction (MAIAC) Collection 6 (C6) and Collection 6.1 (C6.1) aerosol optical depth (AOD) products with 1 km spatial resolution. This study validated and compared C6 and C6.1 MAIAC AOD products with AERONET observations in terms of accuracy and stability, and analyzed the spatiotemporal characteristics of AOD at different scales in China. The results show that the overall accuracy of MAIAC products is good, with correlation coefficient (R) > 0.9, mean bias (BIAS) < 0.015, and the fraction within the expected error (EE) > 68 %. However, after the algorithm update, the accuracy of Terra MAIAC aerosol products C6.1 has significantly decreased. The accuracy of the products varies with the region. The accuracy of C6.1 in North China, Central East China, and West China, is comparable to or even exceeds that of C6, but performs poorly in South China. In addition, the stability of the updated C6.1 MAIAC aerosol products has not seen significantly improvement. The metrics of no product can all meet the stability goals of the Global Climate Observing System (GCOS, 0.02 per decade) in China. C6.1 improves the retrieval frequency in many regions and temporarily solves the problem of AOD discontinuity at the boundaries of different aerosol models in C6, but there are some fixed climatological AOD blocks (AOD = 0.014) in the eastern Tibetan Plateau region. Both C6 and C6.1 can capture similar annual variation characteristics of AOD to those observed at the AERONET sites. The study provides possible references for improving the MAIAC algorithm and building long-term stable aerosol records.

Pyrite-stimulated bio-reductive immobilization of perrhenate: Insights from integrated biotic and abiotic perspectives

Microbes possessing electron transfer capabilities hold great promise for remediating subsurface contaminated by redox-active radionuclides such as technetium-99 (99TcO4−) through bio-transformation of soluble contaminants into their sparingly soluble forms. However, the practical application of this concept has been impeded due to the low electron transfer efficiency and long-term product stability under various biogeochemical conditions. Herein, we proposed and tested a pyrite-stimulated bio-immobilization strategy for immobilizing ReO4− (a nonradioactive analogue of 99TcO4−) using sulfate-reducing bacteria (SRB), with a focus on pure-cultured Desulfovibrio vulgaris. Pyrite acted as an effective stimulant for the bio-transformation of ReO4−, boosting the removal rate of ReO4− (50 mg/L) in a solution from 2.8 % (without pyrite) to 100 %. Moreover, the immobilized products showed almost no signs of remobilization during 168 days of monitoring. Dual lines of evidence were presented to elucidate the underlying mechanisms for the pyrite-enhanced bio-activity. Transcriptomic analysis revealed a global upregulation of genes associated with electron conductive cytochromes c network, extracellular tryptophan, and intracellular electron transfer units, leading to enhanced ReO4− bio-reduction. Spectroscopic analysis confirmed the long-term stability of the bio-immobilized products, wherein ReO4− is reduced to stable Re(IV) oxides and Re(IV) sulfides. This work provides a novel green strategy for remediation of radionuclides- or heavy metals-contaminated sites.

일상생활배상책임보험의 보상요건 및 설명의무에 관한 종합적 고찰 - 청주지법 2022. 12. 22. 선고 2021나55269 판결을 중심으로

Daily life liability insurance is a personal liability insurance sold in the form of a special agreement in addition to long-term insurance products. It is a very useful insurance product that covers damages due to general activities that can occur widely in everyday life with an inexpensive insurance premium of less than 1,000 won. At this time, the concept of 'daily life' means life in 'normal times', and is distinguished from 'job performance' that is for 'maintaining a living' or requires professional knowledge, experience, and skills. Of course, the scope of 'daily life' will be determined according to specific circumstances, but at least in the process of determining it, the group performance and homogeneity of the risk consisting of a large number of unspecified general policyholders should not be impaired. In the case where the insured, who usually suffered from depression and paranoid schizophrenia, jumped from a high-rise building and shocked the victim (plaintiff), who just happened to pass under it, the damage caused by the insured's actions was judged as an accidental accident in the first trial. However, in the target judgment, it was judged that the act of the insured jumping out of the building with the intention of suicide or jumping off was not the “general act that may occur in everyday life” mentioned above, but was difficult to regard as being included in the category of “daily life”. The target judgment rejected the plaintiff's claim for damages, considering that it did not meet the former requirements among the usual life and accidental accidents, which are the representative compensation requirements of the daily life liability special agreement. The insured's above actions outside the certain boundaries of daily life are very valid in that they harm the homogeneity of insurance groups. Furthermore, in this paper, an analysis is conducted to clearly distinguish the concepts of 'daily life' and 'job performance' of the special agreement for daily life liability through various lower court rulings, and the purpose and meaning of a number of reasons for indemnification are considered for each type. The results of this review are linked to the obligation to explain the terms and conditions, which are sharp disputes between the insurer and the insured in the stage of exemption and liability for compensation after an insurance accident. Most of the reasons for exemption from the Special Agreement on Daily Liability for Compensation are subject to the obligation to explain as it directly affects the interests of the policyholder and determines whether or not to conclude a contract depending on whether or not to explain it. However, 'daily life' is a concept accepted by social norms as a daily activity of the general public. Even if the insurer does not explain separately, it is reasonable to assume that the insured can fully predict or understand the contents and is not subject to the obligation to explain. This is especially true considering that the Special Agreement on Daily Liability for Compensation, which is a liability guarantee incidental to long-term non-life insurance products, guarantees various risks in daily life with an insurance premium of less than 100 million won per month.

간병보험 약관의 ‘보험기간 중 보험사고 발생’ 조항에 대한 해석론 - 대법원 2023. 10. 12. 선고 2020다232709, 232716 판결의 평석

The Supreme Court recently rendered a decision on the interpretation of the “occurrence of an insured event during the insurance period” clause in the terms and conditions of long-term care insurance. In this decision, the Supreme Court applied various rules of standard form contract interpretation to lay out a detailed theory of interpretation. As the insurer's liability to pay insurance benefits arises only if the insured event specified in the insurance contract occurs during the insurance period, the determination of whether the insurer’s liability has arisen must be preceded by the interpretation of the “occurrence of an insured event during the insurance period” clause in the insurance terms and conditions that constitute part of the insurance contract. If one finds the grounds for which insurance terms and conditions are binding on the contracting parties in the parties’ mutual agreement, the general principles of legal acts, i.e., contracts, interpretation are applicable to the interpretation of insurance terms and conditions. Additionally, the various rules of standard form contract interpretation specifically provided for in the Act on the Regulation of Terms and Conditions are also applicable. In the case addressed by this article, the Supreme Court’s interpretation of the disputed clause in the long-term care insurance terms and conditions differed from that of the lower and appellate courts. The Supreme Court, adhering to principles of contract interpretation, focused on the wording of the clause in question while also considering the context, including the purpose and intent of long-term care insurance, trade practices and other relevant factors. The Supreme Court further applied the principle of objective interpretation, rooted in the principle of good faith as stipulated in the Act on the Regulation of Terms and Conditions. Consequently, the Supreme Court interpreted the clause stating insurance benefits are payable “if the insured is recognized as eligible for long-term care insurance benefits during the insurance period” to mean that insurance benefits are payable “if the insured receives a long-term care rating from the assessment committee during the insurance period,” in accordance with the wording of the clause. Furthermore, the Supreme Court determined that this interpretation did not violate the principle of good faith beyond the limits of private autonomy, thus ruling out the complete nullification or partial nullification, i.e., validity-preserving interpretative reduction, of the clause. Based on this interpretation, the Supreme Court ruled that if the insured was assessed with a long-term care rating after the insurance period terminated due to the insured’s death, the insured event could not be considered to have occurred during the insurance period, even if it was confirmed that the insured was in a state requiring long-term care during the insurance period, and therefore, the insurer's liability to pay insurance benefits did not arise. This court decision is significant as it is the first to establish a specific interpretation theory for the “occurrence of an insured event during the insurance period” clause in long-term care insurance policies. Given that many long-term care insurance products currently on the market have clauses with similar structures and content, the standards and interpretation methods from this decision are expected to apply to future disputes relating to the insurer's liability to pay insurance benefits under such contracts. Moreover, the court decision is meaningful in that it clearly delineates the limits of validity-preserving interpretative reduction or modifying interpretation.

Implementasi Kepatuhan Syariah terhadap Produk-produk Baitul Mal Wat Tamwil An-Nahdliyyin Gunung Lerang

The objectives of this research are (1) To find out the types of products offered by BMT Nahdliyin Gunung Lerang, (2) To find out the implementation of sharia compliance in BMT Nahdliyin Gunung Lerang products. This research uses a qualitative approach, the data collection techniques used are observation and interviews. The subjects of this research are the administrators and members of BMT Nahdliyin Gunung Lerang, the research objects are the products at BMT Nahdliyin Gunung Lerang. The data analysis techniques in this research are data collection, data reduction, data presentation and drawing conclusions. The results of this research show that: (1) The types of products offered by BMT Nahdliyin Gunung Lerang are, Baitul Ma'al Products: Santri Savings, Short Term Financing and Long Term Financing. Then Baitul Tamwil Products: Livestock and Agriculture, (2) Implementation of sharia compliance for BMT Nahdliyin Gunung Lerang products that meet sharia compliance. Based on the first product, namely student savings using a wadiah or deposit agreement which is in accordance with sharia principles. Then short-term and long-term financing products use a qardh contract which refers to providing loans without any additional rewards or benefits. Furthermore, livestock products use a musyarakah agreement, namely cooperation and joint participation between BMT Nahdliyin and investors. Then agricultural products consisting of chilies, eggplant, bananas and sweet potatoes use a mudharabah contract, which is a form of cooperation between capital owners (shahibul maal) and capital managers (mudharib) in certain projects.

A hybrid ensemble learning merging approach for enhancing the super drought computation over Lake Victoria Basin

This study introduces a novel Hybrid Ensemble Machine-Learning (HEML) algorithm to merge long-term satellite-based reanalysis precipitation products (SRPPs), enabling the estimation of super drought events in the Lake Victoria Basin (LVB) during the period of 1984 to 2019. This study considers three widely used Machine learning (ML) models, including RF (Random Forest), GBM (Gradient Boosting Machine), and KNN (k-nearest Neighbors), for the emerging HEML approach. The three SRPPs, including CHIRPS (Climate Hazards Group Infra-Red Precipitation with Station), ERA5-Land, and PERSIANN-CDR (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate Data Record), were used to merge for developing new precipitation estimates from HEML model. Additionally, classification and regression models were employed as base learners in developing this algorithm. The newly developed HEML datasets were compared with other ML and SRPP products for super-drought monitoring. The Standardized precipitation evapotranspiration index (SPEI) was used to estimate super drought characteristics, including Drought frequency (DF), Drought Duration (DD), and Drought Intensity (DI) from machine learning and SRPPs products in LVB and compared with RG observation. The results revealed that the HEML algorithm shows excellent performance (CC = 0.93) compared to the single ML merging method and SRPPs against observation. Furthermore, the HEML merging product adeptly captures the spatiotemporal patterns of super drought characteristics during both training (1984–2009) and testing (2010–2019) periods. This research offers crucial insights for near-real-time drought monitoring, water resource management, and informed policy decisions.

Market segmentation using predictive technology and shared-service contracts

‘Shared-service contracts’ provided by Original Equipment Manufacturers (OEMs) are a standard feature of capital-intensive, long-life products. In such contracts, OEMs assume a predetermined portion of the products’ long-term failure opportunity costs by conducting routine and breakdown maintenance tasks for their customers. Recently, OEMs have been utilizing predictive technology to improve service productivity. It enables OEMs to reduce failure opportunity costs mentioned while using the data generated to develop products at lower costs. We extend the adverse selection framework to model the market segmentation of products offered with shared-service contracts and predictive technology. Our model includes: (i) the cost of product development and operation, (ii) the failure opportunity cost driven by long-term product failures, (iii) the cost of designing product reliability, and (iv) the cost of incorporating predictive technology, which reduces the first two cost components. Here, the OEM targets a basic and a premium offering at their respective customer types. We find that using predictive technology improves the quality and price of OEM products, thereby increasing their profitability. However, predictive technology enables the OEM to design a product line with lower reliability. In addition, the OEM is more likely to choose a ‘premium-only’ strategy when predictive technology is present.