Continuous Observations Research Articles

Processes and controls of regional floods over eastern China

Abstract. Mounting evidence points to elevated regional flood hazards in a changing climate, but existing knowledge about their processes and controls is limited. This is partially attributed to inadequate characterizations of the spatial extent and potential drivers of these floods. Here we develop a machine-learning-based framework (mainly including the Density Based Spatial Clustering Applications with Noise (DBSCAN) clustering algorithm and a conditional random forest model) to examine the processes and controls of regional floods over eastern China. Our empirical analyses are based on a dense network of stream gauging stations with continuous observations of annual maximum flood peaks (i.e. magnitude and timing) during the period 1980–2017. A comprehensive catalogue of 318 regional floods is developed. We reveal a pronounced clustering of regional floods in both space and time over eastern China. This is dictated by cyclonic precipitating systems and/or their interactions with topography. We highlight contrasting behaviours of regional floods in terms of their spatial extents and intensities. These contrasts are determined by fine-scale structures of flood-producing storms and anomalous soil moisture. While land surface properties might play a role in basin-scale flood processes, it is more critical to capture spatial–temporal rainfall variabilities and soil moisture anomalies for reliable large-scale flood hazard modelling and impact assessments. Our analyses contribute to flood science by better characterizing the spatial dimension of flood hazards and can serve as a basis for collaborative flood risk management in a changing climate.

Duration of In-patient Physical Therapy at a Tertiary Hospital: Implications of a Time and Motion Study

Background and Objectives. Inpatient physical therapy (PT) care entails careful provision of service for individuals across a spectrum of disorders needing evidence-based physical rehabilitation during their hospital admission. The main difficulty is identifying adequate time allocation for safe patient service within an eight-hour working time frame. At a selected tertiary teaching government-run hospital, an arbitrary personnel-population ratio method is used for human resource allocation which may lead to issues in service delivery and healthcare workforce wellness. Apart from patient care, physical therapists also assume non-clinical roles revolving on administration, clinical education, and research. This highlights the importance of identifying the duration of tasks to assess work efficiency and manage time constraints posed by the limitations of the work shift. Practice guidelines may help improve staff workload scheduling, however, there is a lack of available guidelines regarding physical therapy practice in the hospital or acute care setting for developing countries. The purpose of this study was to determine the duration of care for inpatients with musculoskeletal and neurological conditions and administrative tasks, and to determine the relationship of duration of care with months of experience. Methods. A continuous observation time motion study of a typical workday of all physical therapists in an in-patient setting of a tertiary teaching hospital was conducted. An external observer will time the tasks done by the PT. The external observer kept distance from the direct patient encounter to minimize interference that may affect timing. Patients with conditions of different etiologies and functional levels were included. Results. Nineteen physical therapists with a mean experience of 54.63 months were observed. There were no adverse events during the implementation of this study. The total mean time in minutes of management of neurological patients is 37:32, and musculoskeletal patients is 28:30. Time for administrative tasks took an average of 20:33 minutes. There was also a low positive correlation on months of experience and treatment duration for patients with neurologic conditions (p=0.0471). Results showed that the allocated treatment duration is determined to be sufficient for performing PT activities. The optimal number of patients to be decked can also be appropriately determined to optimize resource allocation. Conclusion. Our pilot study attempted to quantify the duration of PT care in an inpatient setting that caters to patients with different diagnosis and varying needs for PT management. Although descriptive statistics and a weak to insignificant correlation was seen in most of the variables, there may be some benefit in gathering more duration data across different acute care settings within the country. Our pilot time and motion study can contribute to the limited evidence of duration of inpatient care that may inform human resource allocation, deliverables prioritization, and employee wellness and development. Figures have been presented which could be the basis for future policy research for management science and resource allocation studies.

The annual cycle and sources of relevant aerosol precursor vapors in the central Arctic during the MOSAiC expedition

Abstract. In this study, we present and analyze the first continuous time series of relevant aerosol precursor vapors from the central Arctic (north of 80° N) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. These precursor vapors include sulfuric acid (SA), methanesulfonic acid (MSA), and iodic acid (IA). We use FLEXPART simulations, inverse modeling, sulfur dioxide (SO2) mixing ratios, and chlorophyll a (chl a) observations to interpret the seasonal variability in the vapor concentrations and identify dominant sources. Our results show that both natural and anthropogenic sources are relevant for the concentrations of SA in the Arctic, but anthropogenic sources associated with Arctic haze are the most prevalent. MSA concentrations are an order of magnitude higher during polar day than during polar night due to seasonal changes in biological activity. Peak MSA concentrations were observed in May, which corresponds with the timing of the annual peak in chl a concentrations north of 75° N. IA concentrations exhibit two distinct peaks during the year, namely a dominant peak in spring and a secondary peak in autumn, suggesting that seasonal IA concentrations depend on both solar radiation and sea ice conditions. In general, the seasonal cycles of SA, MSA, and IA in the central Arctic Ocean are related to sea ice conditions, and we expect that changes in the Arctic environment will affect the concentrations of these vapors in the future. The magnitude of these changes and the subsequent influence on aerosol processes remains uncertain, highlighting the need for continued observations of these precursor vapors in the Arctic.

A Method for Bioluminescence-Based RNA Monitoring Using Split-Luciferase Reconstitution Techniques.

A bioluminescence-based RNA monitoring method in living cells was developed using a split NanoLuc (NLuc) reconstitution technique. For specific recognition of a target RNA sequence, a mutant PUM-HD (mPUM) was used. The method was applied to β-actin mRNA in various cells, including primary cultures of rat hippocampal neurons. It allowed for continuous observation of intracellular localization distribution of the target mRNA in living cells, providing insights into various biological phenomena involving intracellular RNA localization and dynamics.

Analysis of deformation evolution characteristics of the northern Lajishan fault before the Jishishan MS6.2 earthquake based on GNSS observations

A MS6.2 earthquake struck Jishishan Country in Gansu Province on 18 December 2023. The earthquake occurred on the eastern branch of the Northern Lajishan fault (NLJSF) which has never experienced such a violent seismic event in recorded history. In this study, multiple periods of GNSS campaign observation data and continuous observation data are collected to reveal the crustal deformation evolution characteristics of the eastern branch of the NLJSF before the earthquake, focusing on the dynamic behavior of the causative fault, regional strain parameter features, and the variation of GNSS baselines across the NLJSF. Velocity field data show that the differential movement on both sides of the fault zone before the earthquake accumulated energy for the occurrence of the earthquake. Cross-fault profile analyses indicate a noticeable weakening of horizontal shortening on both fault flanks, suggesting a nearing fault lockup. The baseline time series and strain parameter time series results both show that the study area is mainly NEE-trending compression deformation. In addition, before the earthquake, multiple baseline results and strain parameter time series deviated from the linear trend and gradually flattened, indicating a strain accumulation in the study area. The overall crustal deformation evolution shows a relatively high earthquake risk before the Lajishan earthquake.

An optimization method for measuring the stomata in cassava (Manihot esculenta Crantz) under multiple abiotic stresses.

As a gateway for gas exchange, pores regulate the transport of air and water in carbon assimilation, respiration, and transpiration to quickly adapt to environmental changes. Therefore, the study of stomatal movement characteristics of plants is helpful to strengthen the understanding of the mechanism of plant response to multi-environmental stress, and can improve the function of plant resistance to stresses. The stomatal movement of Arabidopsis leaves was observed by staining the stomata with rhodamine 6G, but this method has not been reported in other plant leaf stomata studies. Taking cassava as an example, the correlation between cassava stomatal movement and cassava response to stress was observed by using and improving the staining method. Rhodamine 6G is a biological stain widely used in cell biology and molecular biology. It was found that 1 μM rhodamine 6G could stain the stomata of cassava without affecting stomatal movement (n = 109, p < 0.05). In addition, we proposed that stomata fixed with 4% concentration of formaldehyde after staining were closest to the stomatal morphology of cassava epidermis, so as to observe stomatal movement under different environmental stresses more accurately. Previous methods of measuring stomatal pore size by autofluorescence of cell wall needs to fix the cells for 6 h, but Rhodamine staining can only be observed in 2 min, which greatly improves the experimental efficiency. Compared with the traditional exfoliation method (e.g., Arabidopsis), this method can reduce the damage of the leaves and observe the stomata of the whole leaves more completely, so that the experimental results are more complete. In addition, the method enables continuous leaf processing and observation. Using this method, we further compared four different cassava varieties (i.e., KU50, SC16, SC8, and SC205) and found that there are differences in stomatal density (SD) among cassava varieties, and the difference in the SD directly affects the stress resistance of cassava (n = 107, p < 0.001). This finding has important implications for studying the mechanism of plant response to environmental stress through stomata.

Observed Responses of Gravity Wave Momentum Fluxes to the Madden‒Julian Oscillation Around the Extratropical Mesopause Using Mohe Meteor Radar Observations

AbstractThe 12‐year continuous observation of gravity wave momentum fluxes (GWMFs) estimated by the Mohe meteor radar (53.5°N, 122.3°E) revealed prominent intraseasonal variability around the extratropical mesopause (82–94 km) during boreal winters. Composite analysis of the December‒January‒February (DJF) season according to the Madden‒Julian Oscillation (MJO) phases revealed that the zonal GWMFs notably increased in MJO Phase 4 (P4) by ∼2–4 m2/s2, and a Monte Carlo test was designed to examine the statistical significance. The response in zonal winds lags behind the GWMF response by two MJO phases (i.e., 1/2π), indicating a “force‒response” interaction between them. Additionally, time‐lagged composites revealed that strengthened westward GWMFs occurred ∼25–35 days after MJO P4, coincident with the MJO impact on the zonal winds in the stratosphere. The analysis results also suggested that the mechanism of MJO by which the MJO influences the stratospheric circulation might involve poleward propagating effects of stationary planetary waves with zonal wavenumber one. This work emphasizes the importance of GW intraseasonal variability, which impacts tropical sources from the troposphere to the extratropical mesopause.

Peering into Cloud Physics Using Ultra-Fine-Resolution Radar and Lidar Systems

Abstract Cloud microphysical processes, such as droplet activation, condensational growth, and collisional growth, play a central role in the evolution of clouds and precipitation. Accurate representations of these processes in numerical models are challenging partially due to incomplete understanding of them at the process level arising from limited systematic observations. Most surface-based active remote sensors, including today’s operational cloud radars and lidars, have a resolution on the order of tens of meters. This resolution is insufficient to resolve cloud microphysical processes that manifest at finer (meter and submeter) scales. A new set of ultra-high-resolution ground-based radar and lidar systems have been developed to address this observational gap. The newly developed 94-GHz cloud radar has a range resolution down to 2.8 m, or a factor of 10 finer than typical radars, using a large bandwidth and quadratic phase coding techniques. The lidar has a range resolution down to 10 cm, or a factor of 100 finer than typical lidars, using a time-gated time-correlated single-photon-counting technique. Such high-resolution observations were previously only achievable through in situ aircraft measurements. Even then, aircraft measurements do not permit continuous long-term cloud observation as is possible with ground-based remote sensing instruments. In this study, the first-light cloud observations from the new radar and lidar systems are shown to reveal detailed cloud structures that conventional sensors could only perceive in a bulk sense, thus providing new avenues to investigate cloud microphysical processes and their impact on weather and climate.

Mesoscale eddy in situ observation and characterization via underwater glider and complex network theory.

Mesoscale eddies have attracted increased attention due to their central role in ocean energy and mass transport. The observations of their three-dimensional structure will facilitate the understanding of nonlinear eddy dynamics. In this paper, we propose a novel framework, the mesoscale eddy characterization from ordinal modalities recurrence networks method (MeC-OMRN), that utilizes a Petrel-II underwater glider for in situ observations and vertical structure characterization of a moving mesoscale eddy in the northern South China Sea. First, higher resolution continuous observation profile data collected throughout the traversal by the underwater glider are acquired and preprocessed. Subsequently, we analyze and compute these nonlinear data. To further amplify the hidden structural features of the mesoscale eddy, we construct ordinal modalities sequences rich in spatiotemporal characteristics based on the measured vertical density of the mesoscale eddy. Based on this, we employ ordinal modalities recurrence plots (OMRPs) to depict the vertical structure inside and outside the eddy, revealing significant differences in the OMRPs and the unevenness of density stratification within the eddy. To validate our intriguing findings from the perspective of complex network theory, we build the multivariate weighted ordinal modalities recurrence networks, through which network measures exhibit a more random distribution of vertical density stratification within the eddy, possibly due to more intense vertical convection and oscillations within the eddy's seawater micelles. These framework and intriguing findings are anticipated to be applied to more data-driven in situ observation tasks of oceanic phenomena.

Tourism activities significantly contributed toatmospheric pollutants in a remote town of Tianshan revealed by the continuous observation of two years

The large reduction in tourism activities in 2020 provided a unique opportunity to investigate their contribution on atmospheric pollutants in Bayanbulak, a remote town in Tianshan, China. In this scenic and sensitive region, we measured total suspended particulates (TSP) along with concentrations of polycyclic aromatic hydrocarbons (PAHs), organic carbon (OC), elemental carbon (EC) and water-soluble inorganic ions (WSIIs) during the lockdown in 2020 and compared these to levels in the pre-pandemic period of 2019. The study revealed significant reductions in PAHs, OC, EC, and some WSIIs concentrations during the tourist season (May–October) of 2020 compared with 2019, whereas variations between non-tourist seasons were less pronounced. Furthermore, by comparing pollutant characteristics in tourist seasons of these two years, we found that 5- and 6-ring groups were main PAH constituents in 2019, while 5- and 3-ring groups contributed more to total PAHs in 2020. OC/EC ratio increased from 2019 to 2020, indicating an increase of biomass burning contribution after the lockdown. Using positive matrix factorization, we determined that emissions from tourism-related transportation and combustion of natural gas and coal (mainly for cooking) contributed 21.9% and 46.6%, respectively, to certain atmospheric pollutants in 2019, whereas they decreased significantly to 3% and 19.4% in 2020 with dust and biomass contributions increased substantially. The levels of PAHs, OC, and EC from tourism-related sources were as high as 9.31 ng m−3, 1.28 μg m−3 and 0.11 μg m−3 and decreased by 54.37%, 25.16%, and 9.54%, respectively, compared to 2019. Hence, the impact of tourism must be considered during the assessment of local air pollutant emissions, particularly in remote areas.

사운드 스케이프에서 사운드 디자인으로: 샘플링 패드를활용한 소리 창작 활동 프로그램의 효과

The purpose of this study is to examine the effects of a class that was conducted using soundscapes and editing programs to create and present works related to sound. To achieve this, a 5-month course consisting of two parts and four stages was conducted for pre-service teachers. The first part focused on understanding the concept of soundscapes and exploring the properties of sound, while the second part involved collecting sounds and then using editing programs and sampling pads integrated with artificial intelligence technology to present artistic works. The analysis was conducted using continuous observation and questionnaires in the form of reflections. The research results showed that, first, learners became sensitively attuned to everyday sounds and redefined their relationship with sound and music. Second, the use of sampling pads integrated creation with performance activities, providing new experiences in sound expression. Third, learners developed their own ideas into lesson plans. Overall, it was confirmed that the relationship between sound and musical art is not separate but begins in everyday life and is brought to life through the creator's reflections. Additionally, the meaning gained from the process of creating the work is valued.

Tunnel-induced land subsidence assessment in a densely populated residential area using Sentinel-1 PS-InSAR

Land subsidence detection in residential areas based on advanced remotely sensed data is an effective technique to mitigate catastrophic disasters in time. Synthetic aperture radar (SAR) in spaceborne platforms is a highly sophisticated technique to estimate ground surface subsidence with millimeter accuracy for wide-area observation. SAR is beneficial for large-scale social infrastructure project planning and monitoring in densely populated residential areas. In this study, we applied a permanent scatterer (PS) interferometric SAR (PS-InSAR)-based technique for monitoring land subsidence in a tunnel construction site in the Greater Tokyo Area to investigate tunnel-induced ground surface subsidence. Sentinel-1 repeat-pass SAR data in ascending and descending orbital directions were used for continuous observation. Consecutively estimated interferograms based on repeat-pass SAR data were generated to monitor and detect tunnel-induced land subsidence as well as confirm long-term stability along the tunnel excavation path. A bidirectional displacement of the ground area parallel to the earth’s surface in the east–west direction and perpendicular to the earth’s surface in the up–down direction was estimated at a high-phase consistency location using a PS interferometric stacking technique. The resultant data were then analyzed to detect anomalies in the ground area in the spatiotemporal domains by performing displacement time-series analysis. An area near Higashi-Tsutsujigaoka’s local administrative region in the metropolitan center of Tokyo was observed to have 15-mm subsidence and 30-mm displacement in the east–west direction during August–October 2020. The conventional level survey results in the same ground area showed 15–20-mm subsidence above the tunnel excavation path. The findings of this study offer insights into understanding land subsidence in residential environments.

Simulated Exact Confidence Intervals: With Applications to Censored Exponential Reliability Data

ABSTRACTA method for constructing exact simulated confidence intervals is presented, valid for situations with both discrete and continuous observations. The idea of the method is to invert a data generating function, which needs not be monotone, and where special attention is taken when the data generating function contains jumps. The method is applied to obtain exact confidence intervals for certain types of censored data from exponential distributions. The censoring schemes under study are earlier treated in the literature, and a comparison to these approaches is considered. The connection to fiducial inference is discussed, and a difference in the paradigm of obtaining intervals for the parameter is studied.

Time will tell: time-lapse technology and artificial intelligence to set time cut-offs indicating embryo incompetence.

Can more reliable time cut-offs of embryo developmental incompetence be generated by combining time-lapse technology (TLT), artificial intelligence, and preimplantation genetics screening for aneuploidy (PGT-A)? Embryo developmental incompetence can be better predicted by time cut-offs at multiple developmental stages and for different ranges of maternal age. TLT is instrumental for the continual and undisturbed observation of embryo development. It has produced morphokinetic algorithms aimed at selecting embryos able to generate a viable pregnancy, however, such efforts have had limited success. Regardless, the potential of this technology for improving multiple aspects of the IVF process remains considerable. Specifically, TLT could be harnessed to discriminate developmentally incompetent embryos: i.e. those unable to develop to the blastocyst stage or affected by full-chromosome meiotic aneuploidies. If proven valuable, this application would prevent the non-productive use of such embryos, thereby improving laboratory and clinical efficiency and reducing patient stress and costs due to unnecessary embryo transfer and cryopreservation. The training dataset involved embryos of PGT-A cycles cultured in Embryoscope with a single media (836 euploid and 1179 aneuploid blastocysts and 1874 arrested embryos; 2013-2020). Selection criteria were ejaculated sperm, own (not donated) fresh oocytes, trophectoderm biopsy and comprehensive-chromosome-testing to diagnose uniform aneuploidies. Out-of-sample (30% of training), internal (299 euploid and 490 aneuploid blastocysts and 680 arrested embryos; 2021-2022) and external (97 euploid, 110 aneuploid and 603 untested blastocysts and 514 arrested embryos, 2018 to early 2022) validations were conducted. A training dataset (70%) was used to define thresholds. Several models were generated by fitting outcomes to each timing (tPNa-t8) and maternal age. ROC curves pinpointed in-sample classification values associated with 95%, 99% and 99.99% true-positive rate for predicting incompetence. These values were integrated with upper limits of maternal age ranges (<35, 35-37, 38-40, 41-42, and >42 years) in logit functions to identify time cut-offs, whose accuracy was tested on the validation datasets through confusion matrices. For developmental (in)competence, the best performing (i) tPNa cut-offs were 27.8 hpi (error-rate: 0/743), 32.6 hpi (error rate: 0/934), 26.8 hpi (error rate: 0/1178), 22.9 hpi (error-rate: 1/654, 0.1%) and 17.2 hpi (error rate: 4/423, 0.9%) in the <35, 35-37, 38-40, 41-42, and >42 years groups, respectively; (ii) tPNf cut-offs were 36.7 hpi (error rate: 0/738), 47.9 hpi (error rate: 0/921), 45.6 hpi (error rate: 1/1156, 0.1%), 44.1 hpi (error rate: 0/647) and 41.8 hpi (error rate: 0/417); (iii) t2 cut-offs were 50.9 hpi (error rate: 0/724), 49 hpi (error rate: 0/915), 47.1 hpi (error rate: 0/1146), 45.8 hpi (error rate: 0/636) and 43.9 hpi (error rate: 0/416); (iv) t4 cut-offs were 66.9 hpi (error rate: 0/683), 80.7 hpi (error rate: 0/836), 77.1 hpi (error rate: 0/1063), 74.7 hpi (error rate: 0/590) and 71.2 hpi (error rate: 0/389); and (v) t8 cut-offs were 118.1 hpi (error rate: 0/619), 110.6 hpi (error rate: 0/772), 140 hpi (error rate: 0/969), 135 hpi (error rate: 0/533) and 127.5 hpi (error rate: 0/355). tPNf and t2 showed a significant association with chromosomal (in)competence, also when adjusted for maternal age. Nevertheless, the relevant cut-offs were found to perform less well and were redundant compared with the blastocyst development cut-offs. Study limits are its retrospective design and the datasets being unbalanced towards advanced maternal age cases. The potential effects of abnormal cleavage patterns were not assessed. Larger sample sizes and external validations in other clinical settings are warranted. If confirmed by independent studies, this approach could significantly improve the efficiency of ART, by reducing the workload and patient impacts (extended culture and cleavage stage cryopreservation or transfer) associated with embryos that ultimately are developmentally incompetent and should not be considered for treatment. Pending validation, these data might be applied also in static embryo observation settings. This study was supported by the participating institutions. The authors have no conflicts of interest to declare. N/A.

The case for a Framework for UnderStanding Ice-Ocean iNteractions (FUSION) in the Antarctic-Southern Ocean system

We are in a period of rapidly accelerating change across the Antarctic continent and Southern Ocean, with land ice loss leading to sea level rise and multiple other climate impacts. The ice-ocean interactions that dominate the current ice loss signal are a key underdeveloped area of knowledge. The paucity of direct and continuous observations leads to high uncertainty in the glaciological, oceanographic and atmospheric fields required to constrain ice-ocean interactions, and there is a lack of standardised protocols for reconciling observations across different platforms and technologies and modelled outputs. Funding to support observational campaigns is under increasing pressure, including for long-term, internationally coordinated monitoring plans for the Antarctic continent and Southern Ocean. In this Practice Bridge article, we outline research priorities highlighted by the international ice-ocean community and propose the development of a Framework for UnderStanding Ice-Ocean iNteractions (FUSION), using a combined observational-modelling approach, to address these issues. Finally, we propose an implementation plan for putting FUSION into practice by focusing first on an essential variable in ice-ocean interactions: ocean-driven ice shelf melt.

Periodically asymmetric responses of deep chlorophyll maximum to light and thermocline in a clear monomictic lake: Insights from monthly and diel scale observations

Deep chlorophyll maximum (DCM), a chlorophyll peak in the water column, has important implications for biogeochemical cycles, energy flow and water surface algal blooms in deep lakes. However, how an observed periodically asymmetric DCM response to environmental variables remains unclear, limiting our in-depth understanding and effective eco-environmental management of deep lakes. Based on both monthly field investigations in 2021 and diel continuous observations in 2021–2023 in clear, monomictic Lake Fuxian, Southwest China, the temporal dynamics and drivers of DCM were examined and periodic features of DCM were found, with a formation period (FP, February–July) and a weakening period (WP, August–December). On the monthly scale, although DCM dynamics were partly attributed to thermocline structures, the role of light penetration depths varied with period. In the FP, the influence of light on DCM was direct, i.e., increased depth and thickness but decreased magnitude. Differently, the influence of light mainly occurred by affecting thermocline structures in the WP, where water quality was another important driver. On the diel scale, light was a major reason for a thicker and lower (magnitude) DCM during day than at night, and the response of DCM to environmental factors between the FP and WP differed also more during day. This periodically asymmetric response of daytime DCM not only being caused by light but possibly also related to other physical factors such as lake surface water temperature, wind speed and precipitation. Bayesian network modelling suggested that water darkening and stratification intensification may promote a shallower, thinner and larger (magnitude) DCM in both FP and WP, but achieving such changes in DCM requires different light and thermocline thresholds. Our findings provide new information valuable for modelling DCM and for predicting the related surface algal blooms in deep lakes under climate change and eutrophication.

Factors Influencing Suicidal Ideation in Persons with Physical Disabilities.

Suicidal ideation is a leading indicator of suicide risk, particularly among persons with disabilities, a population at high risk of suicide. This study aimed to identify factors affecting suicidal ideation among persons with physical disabilities in Korea. Data for this cross-sectional study were obtained from the Disability and Life Dynamics Panel. Eight hundred and twenty-eight persons with physical disabilities were extracted from the data, and seven hundred seventy people who responded to the suicidal ideation question were included in the analysis. Chi-square and multivariate logistic regression analyses were employed. The results show a high percentage of suicidal ideation among persons with physical disabilities (18.5%). Among the general characteristics, more women were found to have suicidal ideation than men, and people in their 40s and 60s had a higher rate of suicidal ideation than other age groups. A lower educational level was found to be related to suicidal ideation. After controlling for general characteristics, depression increased the likelihood of suicidal ideation among individuals with physical disabilities. Economic difficulties and disability acceptance did not relate to suicidal ideation. Based on the results of this study, continuous observation of suicidal ideation in people with physical disabilities and early intervention programs for preventing depression and increasing disability acceptance are considered necessary.

Patterns and Drivers of Greenhouse Gas Emissions in a Tropical Rubber Plantation from Hainan, Danzhou

The intensification of global climate change has made the study of greenhouse gas (GHG) emissions increasingly important. To gain a deeper understanding of the emission characteristics and driving factors of nitrous oxide (N2O), carbon dioxide (CO2), and methane (CH4) from rubber plantation soils, this study conducted a 16-month continuous observation in a rubber plantation in Danzhou, Hainan, employing the static chamber method for the monthly sampling and measurement of GHG emissions while analyzing the soil’s physical and chemical properties. The results indicated that the N2O flux exhibited no significant diurnal variation between the dry and rainy seasons, with an average emission rate of 0.03 ± 0.002 mg·m−2·h−1. A clear seasonal trend was observed, with higher emissions in summer than in winter, resulting in an annual flux of 3 kg·hm−2·a−1 (equivalent to 1.9 kg N·hm−2·a−1). N2O emissions were significantly correlated with soil temperature and moisture, explaining 46% and 40% of the variations, respectively, while soil ammonium nitrogen content also significantly influenced N2O and CO2 emissions. The rubber plantation soil acted as a source of N2O and CO2 emissions and a sink for CH2, with lower emissions of N2O and CO2 during the daytime compared to nighttime, and higher CH4 uptake during the daytime. In the dry season, there was a significant positive correlation between N2O and CO2 emissions (R2 = 0.74, p &lt; 0.001). This study reveals the diurnal and seasonal patterns of GHG emissions from rubber plantation soils in Hainan and their interrelationships, providing a scientific basis for the low-carbon management of rubber plantations and GHG mitigation strategies, thereby contributing to attempts to reduce the impact of rubber cultivation on climate change.

An event logic graph for geographic environment observation planning in disaster chain monitoring

Effective geographic environment observation planning is the key to obtain disaster monitoring and warning information. The previous researches can only make observation plans for a single disaster at some specific stages. They are difficult to apply to the dynamic evolution of the disaster chain. Timely and comprehensive geographic environment observation planning is urgently needed to provide high-value monitoring data for the identification and response of secondary disaster chains. Event logic graph (ELG) shows great potential in evolutionary law expression and chain event reasoning. Therefore, this study proposed an observation ELG (OELG), in which events and their logical relationships are modeled as nodes and edges to express the occurrence and development motivation of observation events. The disaster chain observation planning can be transformed into the reasoning of potential continuous observation events. Subsequently, an OELG-based geographic environment observation planning framework was proposed, which realizes the construction, instantiation, and plan reasoning of OELG. The observation planning experiment was carried out taking the flood disaster chain that occurred in Beijing, China and Nordrhein-Westfalen, Germany as examples. The results show that OELG can generate disaster chain observation plan more timely, comprehensively, and continuously than other models, thus providing support for disaster chain risk monitoring and emergency response.

Autonomous tracking of honey bee behaviors over long-term periods with cooperating robots.

Digital and mechatronic methods, paired with artificial intelligence and machine learning, are transformative technologies in behavioral science and biology. The central element of the most important pollinator species-honey bees-is the colony's queen. Because honey bee self-regulation is complex and studying queens in their natural colony context is difficult, the behavioral strategies of these organisms have not been widely studied. We created an autonomous robotic observation and behavioral analysis system aimed at continuous observation of the queen and her interactions with worker bees and comb cells, generating behavioral datasets of exceptional length and quality. Key behavioral metrics of the queen and her social embedding within the colony were gathered using our robotic system. Data were collected continuously for 24 hours a day over a period of 30 days, demonstrating our system's capability to extract key behavioral metrics at microscopic, mesoscopic, and macroscopic system levels. Additionally, interactions among the queen, worker bees, and brood were observed and quantified. Long-term continuous observations performed by the robot yielded large amounts of high-definition video data that are beyond the observation capabilities of humans or stationary cameras. Our robotic system can enable a deeper understanding of the innermost mechanisms of honey bees' swarm-intelligent self-regulation. Moreover, it offers the possibility to study other social insect colonies, biocoenoses, and ecosystems in an automated manner. Social insects are keystone species in all terrestrial ecosystems; thus, developing a better understanding of their behaviors will be invaluable for the protection and even the restoration of our fragile ecosystems globally.