Entire Year Research Articles

Seawater intrusion assessment along the Volturno River (Italy) via numerical modeling and spectral analysis

Surface and groundwater salinization are becoming a significant challenge to inland water quality, negatively affecting people and ecosystems in coastal areas. Even if rivers provide critical pathways for seawater intrusion, this salinization phenomenon has received relatively little attention compared to other salinization mechanisms. To assess the distribution of salinity along the final reach of the Volturno River (Italy), an entire hydrologic year was modeled using the HEC-RAS software. The model was fed with high resolution time-series measurements (time interval of 10 min) of water surface elevations at both river mouth and Cancello Arnone (a hydrometric station located 13 km inland). Field observations and remote sensed data were used to perform the hydrodynamic analysis. The model showed good performance indicators (R2 = 0.878, NSE = 0.870, and MAE = 0.037 m) and well caught hydrometric variation over the simulation period. The tidal component was affected by dissipation moving upstream and showed the capability to shape the salinity profile during dry periods. Whereas during wet periods, even if a strong tidal component is present, the profile is totally regulated by the river discharge. The analysis of the salinity distribution, modelled via the Water Quality module, revealed the massive contribution of the river discharge in limiting seawater intrusion. A correlation between intrusion events and hydrometric stages was established over twenty years (2002–2022), showing a consistent trend between intrusion occurrence and the surface water storage anomaly in the lower Volturno River calculated by Global Land Data Assimilation System (GLDAS) model. Although the 1D approach here used may lead to uncertainties in the reproduction of the involved hydrodynamic and salinization processes, the results are useful for the understanding of seawater intrusion in rivers, and may be utilized to study seawater intrusion in aquifers.

Vitamin D Supplementation During COVID-19 Lockdown and After 20 Months: Follow-Up Study on Slovenian Women Aged Between 44 and 66.

The main objective was to assess the impact of the COVID-19 pandemic on vitamin D supplementation habits and their changes in the follow-up, 20 months after the study in Slovenian premenopausal and postmenopausal women. A cross-sectional study was conducted between March and May 2021. 176 healthy women aged 44 to 65 from the Central Slovenian region were included in the final analysis. Vitamin D status was determined by measuring 25(OH)D concentration. After 20 months an online follow-up questionnaire was sent out, to which 123 participants responded with complete data. Between March and May 2021, 61% of the participants were supplementing vitamin D. 55% of the supplementers and 88% of the non-supplementers had insufficient levels (total 25(OH)D <75 nmol/L). After 20 months in the follow-up, it was found that 62% of participants were taking vitamin D supplements, but only 70% of those who had initially reported taking supplements were still doing so. In the follow-up 61% of participants stated that they started or increased vitamin D intake due to COVID-19. Vitamin D supplementation increased 7-fold compared to pre-pandemic levels and remained at a high level after 20 months. However, a significant number of participants discontinued supplementation, and only one-fifth were taking vitamin D throughout the entire year. Supplementation is effective for vitamin D deficiency prevention only at the individual level, however due to low compliance it should not be the only strategy for preventing vitamin D deficiency in the population.

Pemigatinib for Cholangiocarcinoma– A Novel Drug

Cholangiocarcinoma(CLCA) is a cancer that develops in the narrow tubes known as bile ducts, which transport the digesting fluid bile. This disease, also recognized as Hepatic-duct cancer, is a form of tumor that is extremely difficult to cure with standard chemotherapy. iCLCA refers to cancers that develop within the gastrointestinal tract of the Hepatic-ducts inside the liver and are usually instigated by mutations in the Fibroblast Growth Factor Receptor2 (FiGFR2) gene. Pemigatinib(Pg) is a distinctive, powerful medication that specifically inhibits the action of mutated FGFR2 and is now identified being a viable therapy option for individuals with intrahepatic CLCA. Cholangiocarcinoma (CLCA) is a diverse category of cancers with few therapeutic options. Considering the latest developments in health oncology, CLCA individuals with metastasizing cancer have a terrible prognosis, with an overall median lifespan of barely an entire year. The CLCA health community has made substantial efforts in the recent decade to enhance distinct clinical results by introducing molecularly embattled treatments in this environment. Among some of these therapies, the FiGFR 2 inhibitor Pg has been granted rapid authorization by the USA-Food and Drug Administration (FDA) in CLCA individuals who have FiGFR2 gene combinations or additional rearrangements founded on the outcomes of the FIGHT-202 trial, making it the initial molecularly specific rehabilitation to be endorsed as a remedy of CLCA.This review seeks to present a concise review of pemigatinib's latest advancement, with a precise emphasis on the FIGHT-202 study, the endorsement of this FiGFR inhibitor, and the impending problems related to the routine of FiGFR-directed medicines in CLCA individuals.

The Effect of Demographic Factors (Age, Gender, Sector) on The Covid -19 Infection in Babylon Province / Iraq

Background:&#x0D; The rapid sweep of the Corona virus that the world witnessed during these three years has attracted the attention of scientists to it. Therefore, they tried to get to know it from all sides, in addition to collecting data for the people most vulnerable to the virus, as well as knowing the seasons of the year most suitable for it. The research aimed was to describe the distribution of confirmed cases depending on gender, age, institutions, and months.&#x0D; Materials and Methods:This data was collected for an entire year (January 2021-December 2021) from Public Health Department, and cases were diagnosed based on a test RT-PCR.&#x0D; Results: The result depended on baseline characteristics of confirmed cases (n=42,530), males recorded a higher rate of infection than females(53.32 %)).     According to the registered age groups that were reported in age (less than  1 -more than 65) years, It was found that the age most susceptible to infection ranged between 14-44 (61.21%). While the warm season (spring and summer) had the highest rate of virus infection (17.17%).&#x0D;  Conclusion: research that was some demographic factors important in the development of the covid -19morbidity like age especially in the older, sex male more effect than females, and the sector incrowded places than others sectors .in the warm seasons more infection by corona virus .

COVID-19 Infections and Deaths between Rural and Urban Provinces of Zimbabwe, 2020: A Spatial Variations Analysis

Zimbabwe continues to record new COVID-19 cases as is the case in other countries. Although the Ministry of Health in Zimbabwe continues to publish daily situation reports (SitRep), and regular surveillance updates, no review of existing data has been done to establish the regional trends of the disease over time. This desk review study seeks to analyze the trends (province by province) of the COVID-19 in Zimbabwe for year 2020 in order to establish if spatial variations in infection rates and deaths exist. Ultimately, the aim is to come up with appropriate context-specific prevention and control measures. The study also seeks to establish whether or not there is a difference in COVID-19 infection rates and deaths between urban and rural provinces of Zimbabwe. A historical research design that made use of available secondary data on COVID-19 in Zimbabwe was used. COVID-19 statistics for year 2020 as provided by the Zimbabwe Ministry of Health and Child Care were accessed from the website and reviewed. A hypothesis test to determine if there was a difference in COVID-19 attack rates between urban and rural provinces of Zimbabwe was also done. An independent samples t-test using Microsoft excel was done on cumulative COVID-19 cases data for the entire year 2020. The study revealed that spatial variations in COVID-19 infections and deaths between urban and rural provinces of Zimbabwe existed. Urban provinces recorded more COVID-19 cases in 2020 compared to rural provinces. Keywords: COVID-19, Infection rate, Psychological distress, Spatial, Variations, Vaccine hesitancy.

Seasonal wild dance of dual endosymbionts in the pear psyllid Cacopsylla pyricola (Hemiptera: Psylloidea)

Most sap-feeding insects maintain obligate relationships with endosymbiotic bacteria that provide their hosts with essential nutrients. However, knowledge about the dynamics of endosymbiont titers across seasons in natural host populations is scarce. Here, we used quantitative PCR to investigate the seasonal dynamics of the dual endosymbionts “Candidatus Carsonella ruddii” and “Ca. Psyllophila symbiotica” in a natural population of the pear psyllid Cacopsylla pyricola (Hemiptera: Psylloidea: Psyllidae). Psyllid individuals were collected across an entire year, covering both summer and overwintering generations. Immatures harboured the highest titers of both endosymbionts, while the lowest endosymbiont density was observed in males. The density of Carsonella remained high and relatively stable across the vegetative period of the pear trees, but significantly dropped during the non-vegetative period, overlapping with C. pyricola’s reproductive diapause. In contrast, the titer of Psyllophila was consistently higher than Carsonella’s and exhibited fluctuations throughout the sampling year, which might be related to host age. Despite a tightly integrated metabolic complementarity between Carsonella and Psyllophila, our findings highlight differences in their density dynamics throughout the year, that might be linked to their metabolic roles at different life stages of the host.

Assessment of a deep learning model for monitoring atmospheric pollution: Case study in Antwerp, Belgium

Urban areas face a significant health risk due to atmospheric pollution necessitating continuous monitoring to assess and mitigate its impact and achieve a sustainable city. In this study, a deep learning model was developed and trained using Computational Fluid Dynamics (CFD) simulations to predict the dispersion of nitrogen dioxide (NO2) emissions from traffic. The model’s performance was evaluated by comparing it to real-world field measurements conducted in Antwerp, Belgium, throughout 2016. Temporal comparisons with a traffic-influenced air quality station over the entire year yielded an average correlation coefficient (R) of 0.83 and a mean relative error (MRE) of 0.21. Additionally, a spatial evaluation was conducted by comparing the model’s predictions to a measurement campaign involving 73 samplers. The spatial evaluation resulted in an R of 0.72 and a MRE of 0.18 for samplers located near known emission sources. Notably, the deep learning model demonstrated computational efficiency, outperforming CFD simulations by an order of magnitude of 100 to 1000, enabling real-time pollution monitoring and large-scale scenario studies without compromising the consideration of micro-scale effects that are typically overlooked in larger-scale models.

Application of a concrete thermal pile in cooling the warming permafrost under climate change

Permafrost degradation caused by climate warming is posing a serious threat to the stability of cast-in-place pile foundations in warm permafrost regions. Ambient cold energy can be effectively utilized by two-phase closed thermosyphons (TPCTs) to cool the permafrost. Therefore, we installed TPCTs in a cast-in-place pile foundation to create a unique structure called a thermal pile, which effectively utilizes the TPCTs to regulate ground temperature. And we conducted a case study and numerical simulation to exhibit the cooling performance, and optimize the structure of the thermal pile. The purpose of this study is to promote the application of thermal piles in unstable permafrost regions. Based on the findings, the thermal pile operated for approximately 53% of the entire year and effectively reduced the deep ground temperature at a rate of at least −0.1 °C per year. Additionally, it successfully raised the permafrost table that is 0.35 m shallower than the natural ground level. These characteristics prove highly beneficial in mitigating the adverse effects of permafrost degradation and enhancing infrastructure safety. Expanding the length of the condenser section and the diameter of the TPCT in a suitable manner can effectively enhance the cooling capability of the thermal pile and ensure the long-term mechanical stability of the pile foundation even under climate warming.

Longitudinal carriage of antimicrobial resistant Enterobacterales in healthy individuals in Ireland - Assessing the impact of recreational water use on duration of carriage

The increasing prevalence of extended-spectrum beta-lactamase (ESBL) producing Enterobacterales (ESBL-PE) and carbapenemase-producing Enterobacterales (CPE) is a major public health concern worldwide. Despite the associated risk of infection from gut colonisation with a resistant Enterobacterales, the incidence and duration of carriage in healthy individuals is poorly studied. This “persistence study” is the first in Ireland to assess the longitudinal carriage of ESBL-PE and CPE in healthy individuals. A cohort of 45 participants, 22 of whom were colonised with ESBL-PE, was recruited from a recently completed point prevalence study that investigated colonisation in recreational water users (WU) versus controls. Six bi-monthly faecal samples per participant were analysed for CPE and ESBL-PE over one year and the relationship between persistent colonisation and exposure to natural waters was investigated. For 11 of 45 participants (24.4 %) ESBL-E. coli (ESBL-EC) was detected in at least one sample. Genomic analysis revealed that six participants harboured the same ESBL-EC strains as identified in the preceding study. ESBL-EC persisted in the gut for a median duration of 10.3 months (range 4–23 months), consistent with previous research. Five participants (11.1 %) carried ESBL-EC for the entire study year. The carbapenemase gene blaIMI-2 was detected once. Colonisation was higher in water users during the non-bathing season (n = 10, November 2021–April 2022), than during the bathing season (n = 5, May 2022–September 2022) [relative risk 1.99 (95 % CI 0.34–11.71)]. However, overall WU were less likely to be colonised with ESBL-EC than controls (19 % vs 25 % respectively, RR 0.76, CI 0.24–2.34). Further research is warranted to better understand the factors influencing the persistence of gut colonisation with ESBL-EC and CPE and to what extent bathing water quality impacts colonisation for those regularly exposed.

Optimal scheduling and management of pumped hydro storage integrated with grid-connected renewable power plants

Pumped hydro-energy storage will become a fundamental element of power systems in the coming years by adding value to each link in electricity production and the supply chain. The growth of these systems is essential for improving the integration of renewables and avoiding dependence on fossil fuel sources, such as gas or oil. This paper presents the modeling and application of an optimal hourly management model of grid-connected photovoltaic and wind power plants integrated with reversible pump-turbine units to maximize the monthly operating profits of the energy system and meet electricity demand. The techno-economic dispatch model is formulated as a mixed-integer optimization problem. To assess the proposed model, it is applied to a Spanish case study system, and the results are obtained for an entire year. The combination of renewable energy and pumped hydro energy storage reduces energy dependence by decreasing energy costs by 27 % compared with a system without storage to satisfy the required electricity demand. The findings confirm that storage plays a key role in energy transition to ensure the security and stability of power systems with a higher share of renewable generation.

Integrating monthly spring tidal waves into estuarine carbon budget of meta-ecosystems

The contribution of lateral carbon (C) to hydrological processes is well known for its ecological functions in the estuarine C budget across the terrestrial–aquatic interfaces. However, sampling of individual daily tides during multiple months or seasons in heterogeneous patches of landscape makes extrapolation from days to months or seasons challenging. In this paper, we examine the terrestrial–aquatic lateral hydrological C flux for an estuarine marsh where monthly tides, including consecutive daily spring tides, were measured over the course of an entire year. We found a significant correlation between imported and exported hydrological dissolved C, both dissolved organic carbon (DOC) and dissolved inorganic carbon (DIC), although a similar correlation was not found for particulate organic carbon (POC). Based on a total of 44 sampling trips over a year, this saltmarsh appeared to be a net exporter of DOC and DIC but a net sink of POC. Furthermore, the lateral hydrological C budget functioned as a limited lateral C sink in terms of organic C (i.e., ΔPOC and ΔDOC), while the marsh functioned as a small lateral C source. Our findings highlight the importance of lateral hydrologic inflows/outflows in wetland C budgets of land–water interfaces, especially in those characterized by the meta-ecosystem framework. Surprisingly, different C species responded unequally to the lateral hydrological C budget, suggesting that a conceptual realization of meta-ecosystem is a powerful theoretical framework to extend the outwelling hypothesis.

Tracking social behaviour with smartphones in people with Parkinson's: a longitudinal study

ABSTRACT Parkinson's disease (PD) is a chronic neurological disease that negatively influences patients' quality of life (QoL). Reduced social interactions are a result of both PD symptoms and impairment in QoL, which is known as social withdrawal. Smartphones are suitable for monitoring social behaviour under the notion of digital phenotyping, as people spend significant time socialising on them. We implement year-long longitudinal research using smartphones to study social withdrawal in PD. In addition to an entire year of 24/7 continuous monitoring on smartphones, weekly social ratings and QoL are provided as self-report ground truth. Twenty-three features are extracted from more than 10 million raw data entries collected from eight participants. These features are then used to build models to reflect participants' self-report ratings. We consider the interactions that happen on smartphones, such as calls, messages and social media, and use smartphone sensors to infer face-to-face interactions. By applying multiple linear regression and Naive Bayes, our model is significantly better than just assigning mean and random guesses. The results suggest that our approach provides a more granular method for tracking social behaviour in people with PD via smartphones, and it could benefit wider communities where the social impact on patients needs attention.

Elevated symptoms of depression and anxiety among family members and friends of critically ill COVID-19 patients – an observational study of five cohorts across four countries

Little is known regarding the mental health impact of having a significant person (family member and/or close friend) with COVID-19 of different severity. The study included five prospective cohorts from four countries (Iceland, Norway, Sweden, and the UK) with self-reported data on COVID-19 and symptoms of depression and anxiety during March 2020-March 2022. We calculated prevalence ratios (PR) of depression and anxiety in relation to having a significant person with COVID-19 and performed a longitudinal analysis in the Swedish cohort to describe temporal patterns. 162,237 and 168,783 individuals were included in the analysis of depression and anxiety, respectively, of whom 24,718 and 27,003 reported a significant person with COVID-19. Overall, the PR was 1.07 (95% CI: 1.05-1.10) for depression and 1.08 (95% CI: 1.03-1.13) for anxiety in relation to having a significant person with COVID-19. The respective PRs for depression and anxiety were 1.15 (95% CI: 1.08-1.23) and 1.24 (95% CI: 1.14-1.34) if the patient was hospitalized, 1.42 (95% CI: 1.27-1.57) and 1.45 (95% CI: 1.31-1.60) if the patient was ICU-admitted, and 1.34 (95% CI: 1.22-1.46) and 1.36 (95% CI: 1.22-1.51) if the patient died. Individuals with a significant person with hospitalized, ICU-admitted, or fatal COVID-19 showed elevated prevalence of depression and anxiety during the entire year after the COVID-19 diagnosis. Family members and close friends of critically ill COVID-19 patients show persistently elevated prevalence of depressive and anxiety symptoms. This study was primarily supported by NordForsk (COVIDMENT, 105668) and Horizon 2020 (CoMorMent, 847776).

АГРОНОМИЧЕСКИЕ РИСКИ ЗИМНЕГО ПЕРИОДА В УСЛОВИЯХ СОВРЕМЕННЫХ КЛИМАТИЧЕСКИХ ИЗМЕНЕНИЙ

The paper reveals the causes and consequences of unfavorable conditions for overwintering of winter grain crops on the example of the Moscow region. Unstable winter periods in the recent decades resulting from climate change have often led to the damage or loss of winter grain crops (winter wheat, winter rye, and triticale). Using the difference integral curve of average annual temperatures for the entire year, the growing season (May-September), and the period from September to April, including the winter season, it is shown that warm years and warm seasons have been generally observed since 1987. The sum of negative temperatures, snow depth, frost depth, the number of days with snow cover, the duration of cold periods with air temperatures below 0, -5, -10°C, etc. are analyzed for assessment of the changes in overwintering conditions.

Health Care Costs Associated With Hospice Use For People With Dementia In The US.

Policy makers in the US are increasingly concerned that greater use of the Medicare hospice benefit by people with dementia is driving up costs. Yet this perspective fails to incorporate potential cost savings associated with hospice. We estimated the association between hospice use by people with dementia and health care costs, using Medicare Current Beneficiary Survey data from the period 2002-19. For community-dwelling people with dementia, Medicare costs were lower for those who used hospice than for those who did not, whether hospice enrollment was in the last three days ($2,200) or last three months ($7,200) of life, primarily through lower inpatient care costs in the last days of life. In nursing homes, total and Medicare costs were lower for hospice users with dementia who enrolled within a month of death than for those who did not use hospice. Total costs for the entire last year of life for those who used any days of hospice in the last year compared with no hospice did not differ, although Medicare costs were higher and Medicaid costs lower for those in nursing homes. Medicare policies that reduce hospice access and incentivize hospice disenrollment may actually increase Medicare costs, given that hospice cost savings generally derive from a person's last days or weeks of life.

Analysis of some weather variables' impacts on UHF and VHF receivers in Yenagoa Southern, Nigeria

In this study, the effects of some important meteorological variables, such as temperature, relative humidity, and mean sea level pressure, were assessed on the Ultra High Frequency (UHF) radio signals from Niger Delta Television (NDTV), transmitting at 743.25 MHz UHF, and the Very High Frequency (VHF) radio signals from Nigerian Television Authority (NTA), transmitting at 189.25 MHz VHF, both in Yenagoa, Southern Nigeria, within 6°20'17"N and 5°37’32″E. The Digital Community- Access/Cable Television (CATV) analyzer was used to measure the radio signal strength from NDTV and the radio signal strength from NTA Yenagoa, and a self-implemented weather monitoring device was used to measure the weather variables simultaneously at an equal distance within the Metropolis. Throughout the entire year of 2022, measurements were made continuously every six hours (respectively between 12 am and 1 am, 6 am and 7 am, 12 pm and 1 pm, and 6 pm and 7 pm local time). The results showed that the radio signals from both UHF and VHF television stations were directly proportional to temperature, inversely proportional to relative humidity, and did not follow any specific pattern of proportionality with mean sea level pressure. Inferentially, it was seen that these meteorological factors mostly affected the radio signals from the UHF television station, and that these impacts were stronger during the months with high relative humidity compared to the months with lower relative humidity. But based on these findings, a postulation has been put out that has to be verified further. These findings and the proposed postulation, it is thought, would undoubtedly be beneficial in supporting and directing the management of radio communication networks for planning and other reasons.

Daily stream temperature predictions for free-flowing streams in the Pacific Northwest, USA

Supporting sustainable lotic ecosystems and thermal habitats requires estimates of stream temperature that are high in scope and resolution across space and time. We combined and enhanced elements of existing stream temperature models to produce a new statistical model to address this need. Contrasting with previous models that estimated coarser metrics such as monthly or seasonal stream temperature or focused on individual watersheds, we modeled daily stream temperature across the entire calendar year for a broad geographic region. This model reflects mechanistic processes using publicly available climate and landscape covariates in a Generalized Additive Model framework. We allowed covariates to interact while accounting for nonlinear relationships between temporal and spatial covariates to better capture seasonal patterns. To represent variation in sensitivity to climate, we used a moving average of antecedent air temperatures over a variable duration linked to area-standardized streamflow. The moving average window size was longer for reaches having snow-dominated hydrology, especially at higher flows, whereas window size was relatively constant and low for reaches having rain-dominated hydrology. Our model’s ability to capture the temporally-variable impact of snowmelt improved its capacity to predict stream temperature across diverse geography for multiple years. We fit the model to stream temperatures from 1993–2013 and predicted daily stream temperatures for ~261,200 free-flowing stream reaches across the Pacific Northwest USA from 1990–2021. Our daily model fit well (RMSE = 1.76; MAE = 1.32°C). Cross-validation suggested that the model produced useful predictions at unsampled locations across diverse landscapes and climate conditions. These stream temperature predictions will be useful to natural resource practitioners for effective conservation planning in lotic ecosystems and for managing species such as Pacific salmon. Our approach is straightforward and can be adapted to new spatial regions, time periods, or scenarios such as the anticipated decline in snowmelt with climate change.

Design of Noble-Metal-Free Membrane Electrode Assemblies Based on Metal Chalcogenides for Electrochemical Hydrogen Production Via Alkaline Seawater Electrolysis

The production of large amounts of green hydrogen (H2) by electrochemical water splitting represents one of the key pillars to reach net-zero by 2050. As one of the major drawbacks, both low-temperature proton-exchange membrane (PEM) as well as anion-exchange membrane (AEM) electrolysis still rely on the utilization of noble metals in the catalyst layers driving the evolution of H2 and oxygen (O2) on the cathode (HER) and on the anode (OER), respectively. Beyond that, the requirement for highly pure water feeds to prevent degradation of the cell performance over time was previously addressed as one of the main concerns. In particular, this holds true for arid regions located close to the ocean. Advantageously, these coastal arid zones provide essentially unlimited access to seawater, coupled with ample solar irradiation and wind throughout the entire year.[1]One of the major challenges for direct seawater electrolysis lies in the development of selective catalysts, especially for the anode due to the inherently faster reaction kinetics of the competing two-electron chlorine evolution reaction (ClER). Nickel-iron layered double hydroxides (NiFe-LDH) were identified as active and selective OER electrocatalysts in a previous study[2] by our group. Dionigi et al.[3] recently reported a general design principle for selective seawater electrolysis, in which alkaline pH values > 7.5 are claimed to favor OER over ClER for overpotentials < 480 mV.At the cathode, state-of-the-art electrolyzers utilize Pt-based catalysts for an efficient HER.[2] For direct seawater electrolysis, however, not only the high cost but also the weak stability due to chloride-induced corrosion restrict the applicability of Pt-based electrodes. In our contribution, we thus present noble-metal free catalyst materials based on metal chalcogenides with high HER activity and improved stability in alkaline seawater electrolyte in a single-cell electrolyzer setup. Membrane-electrode assemblies (MEAs) with superior corrosion-resistance by a modification of the porous transport layers (PTLs) for both cathode and anode will be presented, which outperform reference MEAs containing Pt-based cathodes in alkaline seawater electrolysis. The optimized noble-metal-free electrode design (fig. 1) combined with well-controlled electrolyte feeding enables alkaline seawater electrolysis operating at industrially relevant current densities.

Optimizing the battery charging and swapping infrastructure for electric short-haul aircraft—The case of electric flight in Norway

Recent advances in battery technology have opened the possibility for short-haul electric flight. This is particularly attractive for commuter airlines that operate in remote regions such as archipelagos or Nordic fjords where the geography impedes other means of transportation. In this paper we address the question of how to optimize the charging infrastructure (charging power, spare batteries) for an airline when considering a battery swapping system. Our analysis considers the expenditures needed for (i) the significant charging power requirements, (ii) spare aircraft batteries, (iii) the used electricity, and (iv) delay costs, should the infrastructure not be sufficient to accommodate the flight schedule. The main result of this paper is the formulation of this problem as a two-phase recourse model. This is required to account for the variation of the flight schedule throughout a year of operations. With this, both the strategic (infrastructure sizing) and tactical (battery recharge scheduling) planning are addressed The model is applied for Widerøe Airlines, with a network of 7 hub airports and 36 regional airports in Norway. The results show that a total investment of 4412 kW in electricity power supply and 25 spare batteries is needed for the considered network, resulting in a daily investment of €11700. We also quantify the benefits of considering an entire year of operations for our analysis, instead of just one congested day (7% cost reduction) or one average day of operations (31% reduction) at the most congested airport.

Big data–enabled sign prediction for Borsa Istanbul intraday equity prices

This paper employs a big data source, the Borsa Istanbul's “data analytics” information, to predict 5-min up, down, and steady signs drawn from closing price changes. Seven machine learning algorithms are compared with 2018 data for the entire year. Success levels for each method are reported for 26 liquid stocks in terms of macro-averaged F-measures. For the 5-min lagged data, nine equities are found to be statistically predictable. For lagged data over longer periods, equities remain predictable, decreasing gradually to zero as the markets absorb the data over time. Furthermore, economic gains for the nine equities are analyzed with algorithms where short selling is allowed or not allowed depending on these predictions. Four equities are found to yield more economic gains via machine learning–supported trading strategies than the equities' own price performances. Under the “efficient market hypothesis,” the results imply a lack of “semistrong-form efficiency.”