Monitoring Urban Expansion and Loss of Agriculture on the North Coast of West Java Province, Indonesia, Using Google Earth Engine and Intensity Analysis

Uncontrolled urban expansion resulting from urbanization has a disastrous impact on agricultural land. This situation is being experienced by the densely populated and fertile island Java in Indonesia. Remote sensing technologies have developed rapidly in recent years, including the creation of Google Earth Engine (GEE). Intensity analysis (IA) is increasingly being used to systematically and substantially analyze land-use/land-cover (LULC) change. As yet, however, no study of land conversion from agriculture to urban areas in Indonesia has adopted GEE and IA approaches simultaneously. Therefore, this study aims to monitor urban penetration to agricultural land in the north coastal region of West Java Province by applying both methods to two time intervals: 2003–2013 and 2013–2020. Landsat data and a robust random forest (RF) classifier available in GEE were chosen for producing LULC maps. Monitoring LULC change using GEE and IA has demonstrated reliable findings. The overall accuracy of Landsat image classification results for 2003, 2013, and 2020 were 88%, 87%, and 88%, respectively. IA outputs at interval levels for all categories showed that the annual change-of-area rate was higher during 2013–2020 than during 2003–2013. At the category level, IA results showed that the area of agricultural land experienced net losses in both periods, with net loss in 2013–2020 being 2.3 times greater than that in 2003–2013 (∼1,850 ha per year). In contrast, the built-up area made net gains in both periods, reaching almost twice as much in the second period as in the first (∼2,030 ha per year). The transition-level IA performed proved that agricultural land had been the primary target for the expansion of built-up areas. The most extensive spatial distribution of land conversion from agriculture to built-up area was concentrated in the regencies of Bekasi, Karawang, and Cirebon. These findings are intended to provide stakeholders with enrichment in terms of available literature and with valuable inputs useful for identifying better urban and regional planning policies in Indonesia and similar regions.

Wave Intensity Analysis Combined With Machine Learning can Detect Impaired Stroke Volume in Simulations of Heart Failure

Heart failure is treatable, but in the United Kingdom, the 1-, 5- and 10-year mortality rates are 24.1, 54.5 and 75.5%, respectively. The poor prognosis reflects, in part, the lack of specific, simple and affordable diagnostic techniques; the disease is often advanced by the time a diagnosis is made. Previous studies have demonstrated that certain metrics derived from pressure–velocity-based wave intensity analysis are significantly altered in the presence of impaired heart performance when averaged over groups, but to date, no study has examined the diagnostic potential of wave intensity on an individual basis, and, additionally, the pressure waveform can only be obtained accurately using invasive methods, which has inhibited clinical adoption. Here, we investigate whether a new form of wave intensity based on noninvasive measurements of arterial diameter and velocity can detect impaired heart performance in an individual. To do so, we have generated a virtual population of two-thousand elderly subjects, modelling half as healthy controls and half with an impaired stroke volume. All metrics derived from the diameter–velocity-based wave intensity waveforms in the carotid, brachial and radial arteries showed significant crossover between groups—no one metric in any artery could reliably indicate whether a subject’s stroke volume was normal or impaired. However, after applying machine learning to the metrics, we found that a support vector classifier could simultaneously achieve up to 99% recall and 95% precision. We conclude that noninvasive wave intensity analysis has significant potential to improve heart failure screening and diagnosis.

Reciprocal Homer1a and Homer2 Isoform Expression Is a Key Mechanism for Muscle Soleus Atrophy in Spaceflown Mice

The molecular mechanisms of skeletal muscle atrophy under extended periods of either disuse or microgravity are not yet fully understood. The transition of Homer isoforms may play a key role during neuromuscular junction (NMJ) imbalance/plasticity in space. Here, we investigated the expression pattern of Homer short and long isoforms by gene array, qPCR, biochemistry, and laser confocal microscopy in skeletal muscles from male C57Bl/N6 mice (n = 5) housed for 30 days in space (Bion-flight = BF) compared to muscles from Bion biosatellite on the ground-housed animals (Bion ground = BG) and from standard cage housed animals (Flight control = FC). A comparison study was carried out with muscles of rats subjected to hindlimb unloading (HU). Gene array and qPCR results showed an increase in Homer1a transcripts, the short dominant negative isoform, in soleus (SOL) muscle after 30 days in microgravity, whereas it was only transiently increased after four days of HU. Conversely, Homer2 long-form was downregulated in SOL muscle in both models. Homer immunofluorescence intensity analysis at the NMJ of BF and HU animals showed comparable outcomes in SOL but not in the extensor digitorum longus (EDL) muscle. Reduced Homer crosslinking at the NMJ consequent to increased Homer1a and/or reduced Homer2 may contribute to muscle-type specific atrophy resulting from microgravity and HU disuse suggesting mutual mechanisms.

Lightning Evolution and VLF Perturbations Associated With Category 5 TC Yasa in the South Pacific Region

In this paper, we present the D-region ionospheric response during the lifespan (10–19 December 2020) of a severe category 5 tropical cyclone (TC) Yasa in the South Pacific by using the very low frequency (VLF, 3-30 kHz) signals from NPM, NLK, and JJI transmitters recorded at Suva, Fiji. Results indicate enhanced lightning and convective activity in all three regions (eyewall, inner rainbands, and outer rainbands) during the TC Yasa that are also linked to the wave sensitive zones of these transmitter-receiver great circle paths. Of the three regions, the outer rainbands showed the maximum lightning occurrence; hence convective activity. Prominent eyewall lightning was observed just before the TC started to weaken following its peak intensity. Analysis of VLF signal amplitudes showed both negative and positive perturbations (amplitudes exceeding ±3σ mark) lasting for more than 2 hours with maximum change in the daytime and nighttime signal amplitudes of -4.9 dB (NPM) and -19.8 dB (NLK), respectively. The signal perturbations were wave-like, exhibiting periods of oscillations between ~2.2-5.5 hours as revealed by the Morlet wavelet analysis. Additionally, the LWPC modeling of the signal perturbations indicated a 10 km increase in daytime D-region reference height, H¢, and a 12 km decrease in nighttime D-region H¢ during TC Yasa. The D-region density gradients (sharpness), b, showed small perturbations of 0.01–0.14 km-1 from its normal values. We suggest that the observed changes to the D-region parameters are due to the enhanced convection during TC Yasa which excites atmospheric gravity waves producing travelling ionospheric disturbances to the D-region.

Historical Tsunamis of Taiwan in the Eighteenth Century: the 1781 Jiateng Harbor Flooding and 1782 Tsunami Event

This research aims to study two of the historical tsunamis occurred in Taiwan during the 18th century and to reconstruct the incidents. The 1781 Jiateng Harbor Flooding, recorded by the Chinese historical document, Taiwan Interview Catalogue, took place on the southwest coast of Taiwan. On the other hand, the 1782 Tsunami was documented in foreign languages, with uncertainties of the actual time. Reasoning these historical events requires not only carefully examining the literature records but also performing the scenarios that match the descriptions. The Impact Intensity Analysis (IIA) is employed to locate possible regions of tsunami sources in order to reproduce the events. Numerical simulations based on the Cornell Multi-Grid Coupled Tsunami Model (COMCOT) analyze the influence of different types of tsunami generated both by submarine mass failures and seismic activities. Numerical results indicate that the source of the 1781 Jiateng Harbor Flooding is located very possibly at the South South-West side of Taiwan. However, simulation results and historical records put the existence of the 1782 Tsunami in doubt, and the possibility of storm surges could not be ruled out.

Impact of Nisin in Combination with Sodium Benzoate and Calcium Carbonate on the Bacterial and Yeast Population of Coconut Neera (Coconut Inflorescence sap)

A natural sap from mature coconut palm known as coconut neera is enriched with essential minerals and vitamins. Rapid microbial fermentation affects neera processing industries because it spoils the physicochemical properties. There are various methods in preservation that extend the shelf life of coconut neera. The addition of nisin is one of the methods which protect neera against fermentation. Therefore, the study is focused to identify the effective combination of nisin (50 ppm) with preservatives like sodium benzoate (500, and 1000 ppm), and calcium carbonate (2500, and 3000 ppm) at two different combinations in neera. At the end of 21 d, 3000 ppm calcium carbonate with 50 ppm nisin in N4 treatment had an effective reduction of 120 × 105 CFU/ml and 143 × 102 CFU/ml for total bacteria and total yeast count. The reduced microbial survival resulted in the pH of 10.45 ± 0.05, total soluble solids of 15.43 ± 0.12 °Brix, and total acidity of 1.11 ± 0.04 mg/ L, at this combination. The treatment of nisin with 3000 ppm calcium carbonate demonstrated the high red fluorescence bacterial cells than the treatment of nisin with 1000 ppm sodium benzoate. Additionally, the microorganisms in N4 treatment precipitated 65.34% Ca2+ from 79.96% in XRF intensity analysis. The synergistic effect of nisin and calcium carbonate explored their antimicrobial activity against the heterogeneous microbial population in coconut neera. The concentration of 3000 ppm calcium carbonate and nisin 50 ppm preserves the physicochemical and sensory qualities, up to 21 d at 4°C, and offer hope for the industrial-scale implementation.

The Use of Maximum Entropy to Enhance Wave Intensity Analysis: An Application to Coronary Arteries in Hypertrophic Obstructive Cardiomyopathy

Background: Wave intensity analysis is useful for analyzing coronary hemodynamics. Much of its clinical application involves the identification of waves indicated by peaks in the wave intensity and relating their presence or absence to different cardiovascular events. However, the analysis of wave intensity peaks can be problematic because of the associated noise in the measurements. This study shows how wave intensity analysis can be enhanced by using a Maximum Entropy Method (MEM).Methods: We introduce a MEM to differentiate between “peaks” and “background” in wave intensity waveforms. We apply the method to the wave intensity waveforms measured in the left anterior descending coronary artery from 10 Hypertrophic Obstructive Cardiomyopathy (HOCM) and 11 Controls with normal cardiac function. We propose a naming convention for the significant waves and compare them across the cohorts.Results: Using a MEM enhances wave intensity analysis by identifying twice as many significant waves as previous studies. The results are robust when MEM is applied to the log transformed wave intensity data and when all of the measured data are used. Comparing waves across cohorts, we suggest that the absence of a forward expansion wave in HOCM can be taken as an indication of HOCM. Our results also indicate that the backward compression waves in HOCM are significantly larger than in Controls; unlike the forward compression waves where the wave energy in Controls is significantly higher than in HOCM. Comparing the smaller secondary waves revealed by MEM, we find some waves that are present in the majority of Controls and absent in almost all HOCM, and other waves that are present in some HOCM patients but entirely absent in Controls. This suggests some diagnostic utility in the clinical measurement of these waves, which can be a positive sign of HOCM or a subgroup with a particular pathology.Conclusion: The MEM enhances wave intensity analysis by identifying many more significant waves. The method is novel and can be applied to wave intensity analysis in all arteries. As an example, we show how it can be useful in the clinical study of hemodynamics in the coronary arteries in HOCM.