Search Results (16)

This study investigates the dynamic relationship between interest and noninterest income at Azer Turk Bank using quarterly data from 2016Q1–2024Q3. Unit root tests including Augmented Dickey–Fuller (ADF), Kwiatkowski–Phillips–Schmidt–Shin (KPSS), and Fourier–KPSS indicate that both variables are non-stationary in levels but become stationary after first differencing. The Hylleberg–Engle–Granger–Yoo (HEGY) test further shows that both series contain a unit root at the non-seasonal (0) frequency, while no unit roots are detected at the seasonal frequencies (π/2 and 3π/2). Johansen cointegration and the Fourier Autoregressive Distributed Lag (Fourier–ADL) framework confirm the existence of a stable long-run equilibrium. As a key methodological contribution, the study derives explicit Fourier-based Vector Error Correction Model (VECM) equations, enabling the modeling of cyclical deviations around nonlinear trends. Fourier Toda–Yamamoto and Breitung–Candelon frequency-domain causality tests reveal asymmetry: interest income consistently drives noninterest income in the short and medium run, whereas the reverse effect is weak. The results also confirm mean reversion, with deviations from equilibrium corrected within 5.9; 2.5 quarters. Overall, the findings highlight the limited diversification potential of noninterest income and the decisive role of lending in bank revenues, offering both methodological advances and practical guidance for macroprudential policy. Full article

Effective water resource management requires an understanding of the interactions between water and environmental parameters, especially in regions with limited data availability. This study used generalized additive models (GAMs) to investigate the relationship between climatic and hydrological factors, namely river flow, rainfall, air temperature, and physicochemical water quality parameters in the Kiso River, Japan. Seasonal and non-seasonal GAMs models were developed for each water quality parameter, resulting in 7 non-seasonal models and 28 seasonal models based on Japan’s meteorological seasons (winter, spring, summer, fall). The findings demonstrated how seasonal models captured seasonal variability, significantly outperforming the non-seasonal models. For example, turbidity in winter (R² = 0.5030) showed significant improvement compared with non-seasonal models (R² = 0.1470), and organic pollution in fall (R² = 0.4099) increased compared with non-seasonal models (R² = 0.2509). Beyond assessing the influence of environmental drivers on water quality, these findings are crucial in regions with limited data, emphasizing the role of model–based seasonal analysis in identifying high-risk contamination periods, and supporting targeted and effective water management and early warning systems. Full article

Competing macroeconomic hypotheses have been developed to explain the US housing market and possible bubble behavior. We employ both seasonally adjusted (SA) and non-seasonally adjusted (NSA) monthly data for about 30 independent variables to examine alternative macro hypotheses for home prices. Using a neural network model as an atheoretical non-linear approach to capture the relative importance of alternative macro variables, we show that these hypotheses generate different macro relevance. As an alternative to testing housing time series, we focus on bubble identification being hypothesis dependent. Model forecast errors (residuals) identify the potential presence of bubbles through standardized residual CUSUM tests for structural breaks. By testing for housing bubbles from these unstructured models, we generate conclusions on the presence of bubbles prior to the Great Financial Crisis and the post-pandemic periods. Competing macro hypotheses or narratives will generate different conclusions on the presence of bubbles and create bubble identification issues. Full article

Zooplankton abundance patterns exhibit apparent seasonality depending on seasonal variations in water temperature. To analyze the abundance patterns of zooplankton communities, it is necessary to consider the environmental factors that are essential for zooplankton community succession. However, this approach is challenging due to the seasonal variability of environmental factors. In this study, all rotifer species inhabiting a water body were classified into three groups based on their abundance and frequency of occurrence, and decomposition method was used to classify them into groups that exhibit seasonal vs. non-seasonal variability. Multivariate analysis was performed on the seasonal, trend, and random components derived from the classical decomposition method of zooplankton abundance and related environmental factors. This approach provided more precise results and higher explanatory power for the correlations between rotifer communities and environmental factors, which cannot be clarified with a simple abundance-based approach. Using this approach, we analyzed the seasonality-based patterns of the abundance of rotifer species by dividing the environmental factors into those associated with seasonal and non-seasonal variabilities. Overall, the results demonstrated that the explanatory power of redundancy analysis was higher when using the three time series components than when using undecomposed abundance data. Full article

Observations from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions can be used to estimate gravimetric excitation of polar motion (PM), which reflects the contribution of mass changes in continental hydrosphere and cryosphere to PM variation. Many solutions for Earth’s gravity field variations have been developed by institutes around the world based on GRACE/GRACE-FO data; however, it remains inconclusive which of them is the most reliable for the determination of PM excitation. In this study, we present a combined series of GRACE/GRACE-FO-based gravimetric excitation of PM computed using the three-cornered-hat (TCH) method, wherein the internal noise level in a combined solution is reduced to a minimum. We compare the combined series with results obtained from the combined GRACE/GRACE-FO solution provided by COST-G (International Combination Service for Time-variable Gravity Fields) and from the single solution elaborated by the Center for Space Research (CSR). All the gravimetric excitation series are evaluated by comparison with the sum of hydrological and cryospheric signals in geodetically observed PM excitation (called GAO). The results show that by minimizing the internal noise level in the combined excitation series using the TCH method, we can receive higher consistency with GAO than in the case of COST-G and CSR solutions, especially for the non-seasonal oscillations. For this spectral band, we obtained correlations between GAO and the best-combined series as high as 0.65 and 0.72 for the χ₁ and χ₂ equatorial components of PM excitation, respectively. The corresponding values for seasonal oscillation were 0.91 for χ₁ and 0.89 for χ₂. The combined series developed in this study explain up to 68% and 60% of overall GAO variability for χ₁ and χ₂, respectively. Full article

This double-blind, randomized controlled trial assessed bright light therapy (BLT) augmentation efficacy compared with placebo light in treating non-seasonal major depressive disorder. The study participants belonged to a subtropical area (24.5°–25.5°N) with extensive daylight and included outpatients who had received stable dosages and various regimens of antidepressive agents for 4 weeks before enrollment. The outcomes were the 17-item Hamilton Depression Rating Scale, Montgomery–Asberg Depression Rating Scale, and Patient Health Questionnaire-9, which were assessed at weeks 1, 2, and 4. A total of 43 participants (mean age 45 years, ranging from 22–81) were randomized into the BLT [n = 22] and placebo light groups [n = 21]. After a 4-week administration of morning light therapy (30 min/day), depressive symptoms did not reduce significantly, which might be due to the small sample size. Nonetheless, this study had some strengths because it was conducted in warmer climates, unlike other studies, and examined diverse Asians with depression. Our findings suggest that several factors, such as poor drug response, different antidepressive regimens, duration of BLT, and daylength variability (i.e., natural daylight in the environment) may influence the utility of add-on BLT. Researchers may consider these important factors for future non-seasonal depression studies in subtropical environments. Full article

Exploring the relationship between evaporation ($E$)-minus-precipitation ($P$) and sea surface salinity (SSS) is vital for understanding global hydrological cycle changes and investigating the salinity budget. This study quantifies the uncertainty in the relationship between $E-P$ and SSS based on satellite data over the 50°S–50°N ocean from 2012 to 2017 in 140 sets of combinations of $E$, $P$ and SSS. We find that the uncertainty (10%) in the variability of freshwater flux (FWF) over 2012–2017 is smaller than that in SSS (15%). The difference in the combination of sets of “$E$-$P$-SSS” products can lead to the 10% difference in RMSD and 25% difference in area-weighted mean correlation coefficients between SSS tendency and FWF. There is a 24.1~58% area over the global ocean with a significant (p value < 0.05) positive correlation between the FWF and SSS tendency derived from satellite products. The seasonal EMP and SSS tendencies show larger correlation coefficients and lower RMSDs over most sets compared with those on nonseasonal time scales. Large uncertainty in the FWF-SSS tendency relation associated with spread among products prevents the use of one combination of $E$, $P$ and SSS from satellite-based products for salinity budget analysis. Full article

Near-inertial internal waves (NIWs) generated by surface wind forcing are intermittently enhanced below and within the surface mixed layer. The NIW kinetic energy below the surface mixed layer varies over intraseasonal, interannual, and decadal timescales; however, these variations remain unexplored, due to a lack of long-term, in situ observations. We present statistical results on the nonseasonal variability of the NIW kinetic energy 400 m below the surface mixed layer in the southwestern East Sea, using moored current measurements from 21 years. We used long time series of the near-inertial band (0.85–1.15 f) kinetic energy to define nine periods of relatively high (period high) and seven periods of relatively low (period low) NIW kinetic energy. The NIW kinetic energy average at period high was about 24 times higher than that at period low and those in specific years (2003, 2012–2013, 2016, and 2020) and decade (2010s) were significantly higher than those in other years and decade (2000s). Composite analysis revealed that negative relative vorticity and strong total strain significantly enhance NIW kinetic energy at 400 m. The relative vorticity was negative (total strain was positively enhanced) during seven (six) out of nine events of period high. NIW trapping in a region of negative relative vorticity and the wave capture process induce nonseasonal variations in NIW kinetic energy below the surface mixed layer. Our study reveals that, over intraseasonal, interannual, and decadal timescales, mesoscale flow fields significantly influence NIWs. Full article

The special mixed reproductive system, i.e., the ability of an individual plant to develop both open, chasmogamous (CH) flowers adapted to cross-pollination and closed, cleistogamous (CL) flowers with obligate self-pollinating, is a common phenomenon in Viola L. In most sections of Northern Hemisphere violets, cleistogamy is seasonal, and CH and CL flowers develop sequentially in the season. Non-seasonal cleistogamy (simultaneous) is a rare phenomenon in rostrate violets. In the current study, we focused on modification of the CH/CL mating system in V. caspia by environmental conditions, resulting in a gradual switch from temporal cleistogamy, occurring in nature, to simultaneous cleistogamy under greenhouse conditions. V. reichenbachiana with seasonal cleistogamy was the control for V. caspia with the labile seasonal/simultaneous cleistogamy system. In simultaneous cleistogamy, the CH and CL flowers, fruits and seeds developed on an individual plant at the same time on the same branch. The typical difference between CH and CL flowers’ pistils is a straight style ending with a head-like stigma in CH and a curved style in CL adapted to self-pollination. This trait persists in the fruit and seed stages, allowing for easy recognition of fruit of CL and CH flowers in simultaneous cleistogamy. Floral meristems of CH flowers of V. reichenbachiana developed on the rhizome at the end of the growing season under short-day conditions and remained dormant until the following season. The CL floral meristems formed under long-day conditions on elongating lateral branches in the upper leaf axils. The daily temperature influenced the variable CH/CL ratio of V. caspia in nature and greenhouse conditions. Regulation of the CL/CH flower ratio by modifying environmental factors is important for basic research on genetic/epigenetic regulation of cleistogamy and for practical use to produce genetically stable lines of economically important species via CL seeds. Full article

In this study, we calculate the hydrological plus cryospheric excitation of polar motion (hydrological plus cryospheric angular momentum, HAM/CAM) using mascon solutions based on observations from the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) missions. We compare and evaluate HAM/CAM computed from GRACE and GRACE-FO mascon data provided by the Jet Propulsion Laboratory (JPL), the Center for Space Research (CSR), and the Goddard Space Flight Center (GSFC). A comparison with HAM obtained from the Land Surface Discharge Model is also provided. An analysis of HAM/CAM and HAM is performed for overall variability, trends, and seasonal and non-seasonal variations. The HAM/CAM and HAM estimates are validated using the geodetic residual time series (GAO), which is an estimation of the hydrological plus cryospheric signal in geodetically observed polar motion excitation. In general, all mascon datasets are found to be equally suitable for the determination of overall, seasonal, and non-seasonal HAM/CAM oscillations, but some differences in trends remain. The use of an ellipsoidal correction, implemented in the newest solution from CSR, does not noticeably affect the consistency between HAM/CAM and GAO. Analysis of the data from the first two years of the GRACE-FO mission indicates that the current accuracy of HAM/CAM from GRACE-FO mascon data meets expectations, and the root mean square deviation of HAM/CAM components are between 5 and 6 milliarcseconds. The findings from this study can be helpful in assessing the role of satellite gravimetry in polar motion studies and may contribute towards future improvements to GRACE-FO data processing. Full article

Current flood risk management is based on statistical models and assessments of the risk of occurrence over a given time period, although with very short measurement periods, usually following catastrophic events. Ongoing monitoring of basic hydrological (river-water level and streamflow) and climate data are the basis for sustainable water management and long-term flood control planning. The lack of data has proven to be particularly negative during this period of global climate change, when non-seasonal flooding (during summer) is becoming increasingly frequent, and the resulting damage greater. The aim of this study was to analyse the possible use of tree ring width chronologies of trees growing in floodplain areas to reconstruct hydrodynamic variables (river-water level and streamflow). The study analysed the influence of climatic and hydrological variables on the growth of narrow-leaved ash (Fraxinus angustifolia Vahl) in the Sava River basin. The results indicate the significant potential of narrow-leaved ash tree-ring width chronologies to reconstruct the summer streamflows of the Sava River (R² = 0.45). These results can serve to develop long-term data series on the summer streamflows of the river, thereby enabling better insight into its spatial and temporal dynamics with the goal of more successful, sustainable management of floodplain areas. Full article

We analyzed real-time measurements of atmospheric carbon dioxide (CO₂), with total electricity production and nationwide restrictions phases in China, the United States of America, Europe, and India due to the novel coronavirus COVID-19 pandemic and its effects on atmospheric CO₂. A decline of 3.7% in the global energy demand at about 150 million tonnes of oil equivalent (Mtoe) in the first quarter (Q1) of 2020 was recorded compared to Q1 2019 due to the cutback on international economic activities. Our results showed that: (1) electricity production for the same period in 2018, 2019, and 2020 shrunk at an offset of 9.20%, which resulted in a modest reduction (−1.79%) of atmospheric CO₂ to the 2017–2018 CO₂ level; (2) a non-seasonal, abrupt, and brief atmospheric CO₂ decrease by 0.85% in mid-February 2020 could be due to Phase 1 restrictions in China. The results indicate that electricity production reduction is significant to the short-term variability of atmospheric CO₂. It also highlights China’s significant contribution to atmospheric CO₂, which suggests that, without the national restriction of activities, CO₂ concentration is set to exceed 2019 by 1.79%. Due to the lockdown, it quickly decreased and sustained for two months. The results underscore atmospheric CO₂ reductions on the monthly time scale that can be achieved if electricity production from combustible sources was slashed. The result could be useful for cost-benefit analyses on the decrease in electricity production of combustible sources and the impact of this reduction on atmospheric CO₂. Full article

The analysis of synoptic satellite data of total chlorophyll-a (Chl-a) and the environmental drivers that influence nutrient and light availability for phytoplankton growth allows us to understand the spatio-temporal variability of phytoplankton biomass. In the Panama Bight Tropical region (PB; 1–9°N, 79–84°W), the spatial distribution of Chl-a is mostly related to the seasonal wind patterns and the intensity of localized upwelling centers. However, the association between the Chl-a and different physical variables and nutrient availability is still not fully assessed. In this study, we evaluate the relationship between the Chl-a and multiple physical (wind, Ekman pumping, geostrophic circulation, mixed layer depth, sea level anomalies, river discharges, sea surface temperature, and photosynthetically available radiation) and chemical (nutrients) drivers in order to explain the spatio-temporal Chl-a variability in the PB. We used satellite data of Chl-a and physical variables, and a re-analysis of a biogeochemical product for nutrients (2002–2016). Our results show that at the regional scale, the Chl-a varies seasonally in response to the wind forcing and sea surface temperature. However, in the coastal areas (mainly Gulf of Panama and off central-southern Colombia), the maximum non-seasonal Chl-a values are found in association with the availability of nutrients by river discharges, localized upwelling centers and the geostrophic circulation field. From this study, we infer that the interplay among these physical-chemical drivers is crucial for supporting the phytoplankton growth and the high biodiversity of the PB region. Full article

The aim of this study was to derive explicit formulas of the average run length (ARL) of a cumulative sum (CUSUM) control chart for seasonal and non-seasonal moving average processes with exogenous variables, and then evaluate it against the numerical integral equation (NIE) method. Both methods had similarly excellent agreement, with an absolute percentage error of less than 0.50%. When compared to other methods, the explicit formula method is extremely useful for finding optimal parameters when other methods cannot. In this work, the procedure for obtaining optimal parameters—which are the reference value ( $a$ ) and control limit ( $h$ )—for designing a CUSUM chart with a minimum out-of-control ARL is presented. In addition, the explicit formulas for the CUSUM control chart were applied with the practical data of a stock price from the stock exchange of Thailand, and the resulting performance efficiency is compared with an exponentially weighted moving average (EWMA) control chart. This comparison showed that the CUSUM control chart efficiently detected a small shift size in the process, whereas the EWMA control chart was more efficient for moderate to large shift sizes. Full article

Shade-grown coffee (shade coffee) is an important component of the forested tropics, and is essential to the conservation of forest-dependent biodiversity. Despite its importance, shade coffee is challenging to map using remotely sensed data given its spectral similarity to forested land. This paper addresses this challenge in three districts of northern Nicaragua, here leveraging cloud-based computing techniques within Google Earth Engine (GEE) to integrate multi-seasonal Landsat 8 satellite imagery (30 m), and physiographic variables (temperature, topography, and precipitation). Applying a random forest machine learning algorithm using reference data from two field surveys produced a 90.5% accuracy across ten classes of land cover, with an 82.1% and 80.0% user’s and producer’s accuracy respectively for shade-grown coffee. Comparing classification accuracies obtained from five datasets exploring different combinations of non-seasonal and seasonal spectral data as well as physiographic data also revealed a trend of increasing accuracy when seasonal data were included in the model and a significant improvement (7.8–20.1%) when topographical data were integrated with spectral data. These results are significant in piloting an open-access and user-friendly approach to mapping heterogeneous shade coffee landscapes with high overall accuracy, even in locations with persistent cloud cover. Full article