Net Value Research Articles

Pure-quartic noise-like pulse generation and its dynamics in an ultrafast fiber laser

We report on the dynamical generation of pure-quartic noise-like pulses (NLPs) in an ultrafast fiber laser with a net anomalous fourth-order dispersion (FOD). The pure-quartic NLPs can be characterized by the appearance of spectral sidebands on the smooth broad spectra, which are different from conventional NLPs in a net second-order dispersion regime. Moreover, the spectral widths of pure-quartic NLPs are closely related to the intra-cavity net FOD value. This unique observation of the pure-quartic NLPs and their dynamics is further justified by theoretical simulation results, indicating that the existence of the spectral sidebands mainly arises from the large net FOD value within the laser cavity. These findings will further deepen the understanding of the nonlinear soliton dynamics in ultrafast fiber lasers and provide new avenues for exploring the high-order-dispersion pulse behaviors and their applications.

Factors Shaping the Net Asset Value of Saudi Real Estate Investment Trusts

This study investigates the impact of the dividend per unit, loan-to-value ratio (LTV), operating performance, and liquidity on the financial performance of Saudi Real Estate Investment Trusts (REITs), as measured by Net Asset Value (NAV). The study examines a sample of 17 listed Saudi REITs over a five-year period, 2019-2023, resulting in 85 observations. Through multiple regression analysis, the results demonstrate a significant positive relationship between NAV and dividend per unit, operating performance, liquidity, and size as a control variable. In contrast, a negative relationship is found between LTV and NAV. These findings provide important insights for investors and portfolio managers, enhancing their understanding of the key factors that drive the financial performance of Saudi REITs.

Optimizing Investment Portfolio Allocation: Analyzing Trends and Dynamics of Alternative Investments in Estate Planning

Private Equity (PE) plays a unique role in estate planning due to its potential for high returns and complexity. Therefore, understanding its pricing dynamics is essential for effectively incorporating it into an estate plan. The current research examines the complexities of optimizing investment portfolio allocation by analyzing the pricing dynamics of PE funds in secondary markets. The study acknowledges the challenges posed by the inherent risks, illiquidity, and long-term nature of PE investments. It focuses on the impact of PE investments on Limited Partners' (LP) optimal allocations. Typically, LPs commit capital to PE funds, which is gradually called and eventually distributed back to them. The research reveals that the PE investments significantly influence LPs' optimal allocations, with differing strategies being observed among LPs with varying risk aversion levels. The study's findings reveal that PE allocations do not consistently decrease in risk aversion, suggesting the presence of nuanced decision-making processes. Depending on an LP's risk aversion, they adopt one of two distinct investment strategies. A conservative LP, characterized by higher risk aversion, holds relatively more liquid reserves of stocks and bonds compared to illiquid PE investments. This LP tends to be unconstrained and to remain close to an interior optimum, leaving it largely unaffected by the illiquid and long-term nature of PE investments. Moreover, the model extends to incorporate a secondary market for PE partnership interests, allowing an exploration into the implications of trading in this market and the pricing dynamics of the Net Asset Value (NAV) and unfunded liabilities. The proposed analysis provides valuable insights into the intricate interplay between the risk aversion, PE investments, and secondary market dynamics, offering guidance to LPs navigating the complex landscape of alternative investments.

Machine Learning Tool for New Selective Serotonin and Serotonin–Norepinephrine Reuptake Inhibitors

Depression, a serious mood disorder, affects about 5% of the population. Currently, there are two groups of antidepressants that are the first-line treatment for depressive disorder: selective serotonin reuptake inhibitors and serotonin–norepinephrine reuptake inhibitors. The aim of the study was to develop Quantitative Structure–Activity Relationship (QSAR) models for serotonin (SERT) and norepinephrine (NET) transporters to predict the affinity and inhibition potential of new molecules. Models were developed using the Automated Machine Learning tool Mljar based on 80% of the dataset according to 10-fold cross-validation and externally validated on the remaining 20% of data. The molecular representation featured two-dimensional Mordred descriptors. For each model, Shapley additive explanations analysis was performed to clarify the influence of the descriptors on the models’ predictions. Based on the final QSAR models, the following results were obtained: NET and pIC50 value RMSEtest = 0.678, R2test = 0.640; NET and pKi RMSEtest = 0.590, R2test = 0.709; SERT and pIC50 RMSEtest = 0.645, R2test = 0.678; SERT and pKi value RMSEtest = 0.540, R2test = 0.828. QSAR models for serotonin and norepinephrine transporters have been made available in a new module of the SerotoninAI application to enhance usability for scientists.

Difference Analysis of Coal Carbon Emission Coefficient in China and Its Effects on Carbon Emission Calculation, Quota Allocation, and Enterprise Costs

China is a leading producer and consumer of coal, with coal being the dominant energy source. The accurate calculation of the mass carbon emission factor (EFm) of coal is crucial as the carbon emissions from its combustion influence carbon emission assessment and policy formulation. However, discrepancies in EFm values across documents, due to varying net calorific values (NCVs), carbon contents (CCs), and carbon oxidation factors (COFs), have posed challenges for enterprises in carbon emission calculations. By analyzing different coal types, it is found that for anthracite, the EFm difference in different documents can reach 38.5%; for bituminous coal, it can reach 42.3%; and for lignite, it can reach 18.6%. These differences significantly affect carbon emission calculation accuracy, carbon allowance allocation fairness, and enterprise costs under the Carbon Border Adjustment Mechanism (CBAM). For instance, in 2023, the calculated carbon emissions of anthracite vary by over 300 million tons depending on the EFm used. To address these issues, relevant departments should establish a unified EFm release system, build a data sharing platform, and standardize enterprise testing standards to enhance the accuracy of carbon-related calculations and drive the low-carbon development of the coal industry.

The Hidden Value of Adult Informal Care in Europe.

The hidden value of adult informal care (IC) refers to the unaccounted value of informal care in overall costs of long-term care (LTC) estimates. This paper estimates the net value of adult IC in Europe, drawing on a well-being-based methodology. We use an instrumental variable strategy and a longitudinal and cross-country dataset to estimate the causal effect of the extensive and intensive margin of caregiving on subjective well-being. We estimate the so-called compensating surplus (CS), namely the income equivalent transfer, to compensate for the net disutility of caregiving. We show that IC reduces average subjective well-being by about 1% compared to the mean (6% among co-residential caregivers). Relative to a country's Gross Domestic Product (GDP), the value of IC ranges between 4.2% in France and 0.85% in Germany. Such relative value declines as the country's share of formal LTC spending increases. These results call for a reconsideration of the existing classifications of LTC regimes. We estimate that the average CS per hour for IC is 9.55€, with a range from 22€ per hour in Switzerland to 5€ per hour in Spain. Additionally, we estimate that the long-term CS (estimated using an individual's permanent income) tends to be lower than short-term CS (estimated using an individual's current income).

INFORMATION DESIGN IN ALLOCATION WITH COSTLY VERIFICATION

AbstractWe study information design in a single‐agent allocation problem with costly verification, where the principal has a positive reservation value. The agent learns privately a signal about the principal's allocation value, drawn from a distribution controlled by an information designer. Given the signal distribution, the principal designs a mechanism to maximize her net value. We show that the agent‐optimal information pools high values at a signal just worth verification, whereas the principal‐optimal information features full disclosure. Moreover, any agent‐optimal information is principal‐worst, despite their partially aligned interests and the absence of transfers.

SAC, PRICE e MITOS

This article aims to discuss the equivalence of the most widely adopted amortization systems in Brazil: SAC and PRICE. Within the approach, a partial view is presented that implies the feeling of non- equality between the two methods when analyzing only the amounts paid throughout the historical series of settlement of a debt balance without considering the value of the installments updated by rates and interest. For demonstration purposes, examples and spreadsheets are presented that indicate the equivalence of cash flows in each of the financing methods and, finally, a general demonstration, which proves that the same principal value remains the same since the act of contracting the financing as well as in the last payment period, when the values of each of the installments, both in SAC and PRICE, are taken to the net future value, generating equality of the debt situations.

A GIS-Based Estimation of Bioenergy Potential from Cereal and Legume Straw Biomasses in Alentejo, Portugal

Portugal exhibits a large deficit in cereals with an import/export ratio of about 18%. Alentejo is a southern vast plain region, which is the largest cereal producer in the country, with about 80% of the total cereal area. The region also shows a huge local energy deficit with a ratio of about 17% between spent and produced energy. In this context, this work used GIS modeling based on available digital geographical information on soil and topographic conditions in Alentejo for estimating optimal production areas of four main classes of cereal and legume classes, which were wheat, barley, oat/lupin, and triticale/broad bean. The estimated areas were validated by 199 sample points in the field and allowed to quantify a potential of bioenergy production from straw biomasses based on yields of biomass net calorific values of 18 MJkg−1 and yields of 6, 9, 6, and 9 tons/ha for the four classes in the order indicated. The estimated areas allocated to the cereal and legume classes covered approximately four municipalities in the region. The total modeled area in Alentejo for the four cultivation classes was 44,980 ha. The results showed that even if 50% of the estimated total straw biomass produced was used for animal feed, the estimated bioenergy production of the remaining half biomass would be of about 2940 TJy−1, or about 12.5% of the actual regional energy production, which is an energy amount able to supply 35 organic Rankine cycle (ORC) 2.5 MW cogeneration units and 347 boilers with 125 kW thermal power, delivering renewable electricity to the grid, and heating facilities as diverse as buildings, nursing homes, or horticultural greenhouses. More than 160 kton of CO2 fossil emissions would also be avoided, delivering a contribution to mitigating effects of climate change. By contributing to the reduction of the large cereal dependence and the carbon emissions of the country, the proposed strategy would contribute to increasing the decentralized bioenergy production for applications in buildings and local facilities, significantly boosting the socio-economic dynamics of rural areas involved.

Do the Macroeconomic variables influence Exchange Traded Funds (ETFs)?

Exchange Traded Funds (ETFs) are essentially Index Funds that are listed and traded on exchanges like stocks. Until the development of ETFs, this was not possible before. Globally, ETFs have opened a whole new panorama of investment opportunities to Retail as well as Institutional Money Managers. They enable investors to gain broad exposure to entire stock markets in different Countries and specific sectors with relative ease, on a real-time basis and at a lower cost than many other forms of investing. An ETF is a basket of stocks that reflects the composition of an Index, like S&P CNX Nifty or BSE Sensex. The ETFs trading value is based on the net asset value of the underlying stocks that it represents. Think of it as a Mutual Fund that you can buy and sell in real-time at a price that change throughout the day. Compared to mutual funds, ETFs are relatively new. The first U.S. ETFs were created by State Street Global Advisors with the launch of the S&P 500 depositary receipts, also known as SPDRs ("spiders"). Although the first ETFs tended to track broad market indexes, more recent ETFs have been developed to track sectors, fixed income, global investments, commodities and currencies. There exists correlation between ETF and macroeconomic variables and also change in independent variables causes change in dependent variable. However, the degree of variability differs. These variables form significant part and the level of prediction is also good. Therefore, the model is good fit for the data. An investor needs to guise into these while taking investment decision.

A Clinical Nomogram for Predicting Substandard Serum Valproic Acid Concentrations in Chinese Patients With Epilepsy.

It is well-known that substandard serum valproic acid (VPA) concentrations may lead to treatment failure of epilepsy. However, there is still a lack of a quick method to predict whether a patient's serum VPA concentration will reach the standard. The aims of this study were to investigate the factors leading to substandard serum VPA concentrations in Chinese patients with epilepsy and develop a related nomogram for risk prediction. From January 2019 to March 2022, a total of 1143 serum VPA concentrations were collected from 630 hospitalized Chinese patients with epilepsy who were monitored by the Department of Pharmacy of Lu'an People's Hospital, and complete clinical data were collected from the corresponding patients for retrospective analysis. All monitored serum VPA concentrations were further divided into a training cohort and a validation cohort. For the training cohort, serum VPA concentrations below 50 µg/mL and between 50 and 100 µg/mL were classified into the subtherapeutic group and therapeutic group, respectively. The variables were selected from the clinical data, and differences between the variables of the subtherapeutic and therapeutic groups were analyzed. The influencing factors leading to substandard serum VPA concentrations were screened via logistic regression analysis, and the screened influencing factors were used to establish the nomogram prediction model. Multivariate logistic regression analysis revealed that the daily dose per unit of body weight (mg/kg/d), route of administration, presence of hepatic lesions, hypoalbuminemia, and combination with carbapenems or barbiturates were independent factors influencing the occurrence of substandard serum VPA concentrations. On the basis of the results of the multivariate logistic regression analysis, a nomogram risk prediction model for substandard serum VPA concentration was established. The values of the C-index and internal verification results indicated that the nomogram model had good accuracy and discrimination. The decision curve revealed that the nomogram that predicted the risk of substandard serum VPA concentration had a greater net benefit value (ranging from 12% to 94%), indicating that the model had a wide prediction interval. Our study established a nomogram risk prediction model for substandard serum VPA concentrations in Chinese patients with epilepsy, which can help doctors or patients control the serum VPA concentration within the target concentration range as soon as possible.

Net buffer load during regional citrate anticoagulated continuous renal replacement therapy.

Regionally anticoagulated continuous renal replacement therapy with citrate is the first choice for critically ill patients with acute kidney injury. If citrate that reaches the patient exceeds the metabolic capacity, metabolic alkalosis will follow. Bicarbonate from the treatment fluids will also reach the patient and add to the bicarbonate load. Net buffer load is a parameter calculated by the dialysis machine software from the treatment fluid contents, the fluid flows and the filter properties. Each time the treatment settings are altered the net buffer load will be re-calculated. This parameter is integrated as a static safety parameter in the Prismax version 3 software, and will guide the operator on a possible development of metabolic alkalosis with the current settings. Algorithms for estimating the net buffer load were developed. Hourly clinical data from electronic medical records from 60 patients' continuous renal replacement treatments at the Adult Intensive Care Unit, Skåne University Hospital, Lund, Sweden was used to simulate net buffer load. The relation between net buffer load and acid base status at steady state was evaluated. Net buffer load was also calculated from three previous studies for comparison to our present cohort. The mean net buffer load was +0.09 ±0.04 mmol/h/kg in the present cohort, and comparable to historic cohorts from literature. We could not establish a correlation to steady state arterial bicarbonate. The pre blood pump citrate containing replacement fluid flow rate was affecting net buffer load most of all parts of the dialysis circuit, with a r2 Pearson correlation coefficient of 0.65 (p<0.001). The net buffer load parameter can alert the operator on the expected impact of the dialysis circuit on patient's acid base status. It was possible to calculate realistic net buffer load values during 60 CRRT treatments.

ECONOMIC VALUE ADDED AND FIRM VALUATION IN NIGERIA

This study examines the impact of economic value added on firm valuation in Nigeria. The study uses three proxies to capture firm valuation. They include income base of firm valuation that is measured as discounted cash flow (DCF), asset based of firm valuation using net book value (NBV) and market-based approach of firm valuation using publicly traded prices in the stock exchange (SP), while the explanatory variables (EVA) was measured as the company’s profit after full cost of capital, while Firm size (FZE) and Leverage (LVG) are use as control variable. The study shows that EVA has a significant effect on firm valuation. The study recommended that successful value-based management firms should maintain that the technical accounting requirement of EVA is straightforward and makes only minimal adjustments to their accounting procedures. To give investors a normal return on their investment in the company's shares, managers should work to boost future EVA.

Tracing value from social determinant solutions.

We develop and illustrate a framework to trace value from social determinants of health (SDOH) interventions across 4 dimensions: health, cost and quality, engagement, and equity. To provide context, we begin by estimating the societal value lost to premature deaths from homelessness and food insecurity, using recent longitudinal methods that offer greater precision. We then apply the value tracing framework to 2 example interventions: permanent supportive housing for chronically homeless people and medically tailored meals for dual eligibles. These examples are supported by a narrative review of relevant literature, highlighting evidence from high-quality studies of SDOH projects that often show a broader range of benefits to multiple stakeholders. Prior research frequently overlooks non-healthcare savings, concluding that interventions "don't pay for themselves." In contrast, our findings show that when all beneficiaries are considered, many SDOH interventions yield a net positive value. Recognizing the public good nature of SDOH interventions is essential for reaching accurate policy conclusions. This paper advocates for greater recognition and estimation of the multiple sources of value in payment policies and investment decisions. Additional SDOH interventions and practical examples for local coalitions are provided in appendices.

Performance analysis of mixing syngas from biomass gasification on the combined cycle power plant

A combined cycle power plant coupled with biomass gasification system is proposed in this present research. The thermodynamic analysis is performed by the impact factor of the mixing ratio and the equivalence ratio. The results show that, with the increase of the mixing ratio from 0 to 50%, the syngas flow from biomass gasification increases from 0 to 54.20 kg/s. The inlet airflow decreases from 654.6 kg/s to 576.3 kg/s. The temperature of the flue gas increases from 586.5?C to 591.4?C. Besides, the power output of the gas turbine increases from 260.51 MW to 264.61MW, while, the power output of the steam turbine drops from 131.05 MW to 126.89 MW. Additionally, with the equivalence ratio increasing from 0.20 to 0.40, the H2 composition decreases from 3.01 % to 1.53 % and the CO composition drops rapidly from 23.75 % to 10.44 %. The net calorific value of the syngas decreases from 6709.85 kJ/kg to 3369.03 kJ/kg, the mass flow rate of both the syngas and the flue gas increase from 6.88 kg/s to 9.02 kg/s and from 575.17 kg/s to 601.00 kg/s, respectively. Besides, the power output of the gas turbine increases from 264.49 MW to 270.17 MW, while, the power output of the steam turbine drops from 127.01 MW to 121.28 MW.

Indonesia's country-specific CO2 emission factor based on gas fuels for greenhouse gas inventory in the energy sector.

Indonesia currently calculates CO2 emissions from gas fuels using Tier 1 emission factors adopted from the Intergovernmental Panel on Climate Change (IPCC). However, this method may not accurately capture the country's specific emission characteristics. To address this, this study aims to derive country-specific CO2 emission factors for gas fuels, including liquefied petroleum gas (LPG), liquefied gas for vehicles (LGV), natural gas (NG), and liquefied natural gas (LNG), by analyzing fuel samples collected nationwide. A total of 128 LPG samples from 25 regions, 5 LGV samples from 2 regions, 23 NG samples from 11 regions, and 2 LNG samples from 2 regions were analyzed. Emission factors were determined based on gas composition, carbon content, and net calorific value. The uncertainties were calculated to reflect the contributions of all key parameters in the emission factor calculation. The results show that LPG has the highest EF Tier 2, while LNG has the lowest. The average country-specific CO2 emission factors for Indonesia are 65.41 ± 0.67 tCO2/TJ for LPG, 64.89 ± 0.07 tCO2/TJ for LGV, 57.64 ± 10.18 tCO2/TJ for NG, and 57.27 ± 9.50 tCO2/TJ for LNG. We expect stakeholders to incorporate these EF Tier 2 values into greenhouse gas reporting, enabling more accurate assessments of carbon footprints, supporting evidence-based policymaking, and strengthening Indonesia's climate action efforts.

The Influence of Marketing Costs and Production Costs on Net Profit of Food and Beverage Subsector Manufacturing Companies Listed on The Indonesian Stock Exchange 2020-2023

Net profit is one of the leading indicators in investment decision-making. Companies that have a high net profit value are believed to provide prosperity for investors. A company's net profit is obtained from revenue minus costs. The most significant cost components in the food and beverage sector industry profit and loss report are marketing costs and production costs. Thus, these two costs need to be managed well in order to support maximum net profit. This research aims to find out how marketing costs and production costs influence increasing profits in Food and beverage subsector Manufacturing Companies Listed on the Indonesia Stock Exchange. This research used 64 data samples. The results of this research analysis state that marketing costs can have a positive influence on the company's net profit. Likewise, production costs have been proven to have a positive influence on the company's net profit. It is hoped that the results of this research can provide consideration for decision-makers, such as managers and investors, that marketing costs and production costs that can be managed well can contribute to increasing the company's net profit

CAPTURE FISHERIES BUSINESS ANALYSIS OF THE TROLL LINE FISHING FLEET AT THE PALABUHANRATU ARCHIPELAGO FISHING PORT, SUKABUMI, INDONESIA

The troll line fishing fleet is one of several capture fisheries business units often found at the Palabuhanratu Archipelago Fishing Port, Sukabumi, Indonesia. The Sukabumi Central Capture Fisheries Statistics Agency noted a decrease in trolling boats catching and landing fish at the Palabuhanratu Archipelago Fishing Port in the last ten years. This condition allegedly indicates a decline in income for the capture fisheries business players. This research evaluated the net income value of the catch fisheries business unit of the troll line fishing fleet at the Palabuhanratu Archipelago Fishing Port. Data was collected using survey and interview methods from January to March 2023. The purposive sampling method highlighted that 15 respondents consisting of ship owners, captains, and crew members of fishing boats were appointed as sources for this research. Analysis of the fishing business of the Troll Line fishing fleet evaluates the average net income value as 636,496,667 IDR/vessel/year. This net income value is distributed among seven business actors consisting of ship owners (317,596,429 IDR/year), a captain (95,278,929 IDR/year), and four crew members (55,579,375 IDR/person/year). The evaluation value of net income indicates that the fisheries business unit caught by the troll line fishing fleet at the Palabuhanratu Archipelago Fishing Port still has quite promising profits for all business actors.

Revalorisation of Vine Pruning Waste Through the Production of Zero CO2 Emission Charcoal

This research studies the production of charcoal from a by-product of viticulture such as the vine pruning remains of vine (vine shoots). During this study, several carbonisation tests were carried out in an electric muffle furnace where vine shoot samples were tested at different temperature ranges (150–450 °C) and with test durations of 2 h and 3 h. From these tests, the mass yields and carbon yields were studied, as well as the characterisation of the chemical composition of the resulting charcoals, obtaining the maximum results of the fixed carbon content of up to 80.4%. Subsequently, the tests’ energy consumptions were also recorded in order to optimise the amount of grammes of carbon per kWh of energy used. The average value obtained in the trials was 18.55 g of carbon per kWh of energy used in the carbonisation process. Finally, special emphasis was placed on studying the sustainability of this charcoal through the net balance of CO2 eq emissions. To this end, the CO2 eq emissions associated with the energy consumption of the trials and how, through the use of this waste to produce 10–12 g of charcoal, the negative net emission values of up to −522.74 g of CO2 eq were achieved were evaluated. This demonstrates the possibility of charcoal production with a zero-carbon footprint. This acts as evidence of the possibility of zero carbon footprint charcoal production, a key innovative aspect that helps to achieve greater sustainability in industrial sectors with a high impact on the region.

EVALUASI EFEKTIVITAS TATA KELOLA SAMPAH DI TEMPAT PENGOLAHAN SAMPAH TERPADU (TPST) TOSS CENTER GEMA SANTI KABUPATEN KLUNGKUNG

Despite various national and regional waste management efforts, the outcomes remain suboptimal, particularly in facilities like TPST and TPS3R. This study evaluates the effectiveness of waste management at TPST TOSS Center Gema Santi in meeting the 2025 JAKSTRADA targets, focusing on waste reduction and handling, cost-benefit analysis (CBA), and human resource (HR) competencies. From January 2023 to April 2024, the facility achieved a combined waste reduction and handling rate of only 15.7%, with a ZWI score of 0.11 in 2023 and 0.06 from January to April 2024. The CBA for the same period showed a BCR of 0.23 and a net value of -Rp1,293,846,839. HR competency was found to be strong in terms of knowledge, attitude, and practice. In conclusion, TPST TOSS Center Gema Santi has not met the 2025 JAKSTRADA targets of 30% waste reduction and 70% waste handling, primarily due to operational inefficiencies where costs outweigh benefits. However, the strong HR competencies suggest potential for improvement. Key recommendations include strengthening waste management policies, promoting waste sorting at the source, fostering collaboration with stakeholders, adopting automated technologies for operations, and providing continuous training to enhance HR capacity. Keywords: TPST; Evaluation; Waste management effectiveness; HR Competency