Index Monitoring Research Articles

Meteorological Drought Analysis Using Multiple Indices for Selected Stations in Iraq

This study aims to assess the performance of three drought indices for drought monitoring to study the characteristics of meteorological drought in Iraq, which are the Standard Precipitation Index (SPI), the China-Z Index (CZI), and the Modified China-Z Index (MCZI) on 1-, 3-, 6-, 9-, and 12-month timescales, using monthly precipitation data from 1980 to 2021. These indices were used to analyze the spatiotemporal dynamics of droughts using the rainfall data collected from five meteorological stations scattered across the four climatic zones as classified by Köppen in Iraq. According to the study, the Pearson correlation coefficient (r) values among the indices increase with increasing time scale and give similar drought characteristics at the 9-month and 12-month time scales. SPI generally indicated the drought event earlier and with more severe characteristics than the other indices. MCZI showed wetness earlier than the other two indices, and it also described the drought categories similarly to SPI and CZI, especially in the northern regions of Iraq, but it was less official in describing it as we headed down to the south. While CZI described the drought as having less severity than SPI, it frequently gives the same classifications of drought as SPI. CZI could be used as a good meteorological drought monitor, depending on the month, the length of the drought duration, and the climatic conditions of the region. It might be an alternative to the SPI, which needs long rainfall records and has a complicated structure. SPI and CZI can be considered good indices for describing drought in all regions of Iraq. The result shows that 1980, 1993, 1995, and 2019 were the most wet years; 2007–2010 was the most severe drought event; and Iraq's climate was normal to moderate drought during the studied period for all considered stations.

Role of rainfall temporal distribution on effective infiltration in the loess slope and prediction model

Rainfall is one of the main causes of landslides, particularly in the Loess Plateau. When rainfall occurs, rainfall thresholds can be used to predict whether it will cause landslides in monitoring and early-warning system. However, most rainfall thresholds are established based on constant rainfall processes. Therefore, this study takes the temporal distribution of rainfall into account in rainfall threshold studies and proposes four well-delineated temporal distribution types and an innovative three-step model. Rainfall thresholds are derived from 45 months of rainfall data and slope moisture data obtained through in-situ monitoring of the loess slope in Yan'an city, northwest China. Our analysis focuses on effective rainfall infiltration rather than shallow landslides as the monitoring index for thresholds. The results revealed a total of 189 rainfall events over the course of 45 months. Among these, 167 were classified as ineffective rainfall events with an infiltration depth of <10 cm, while 22 were categorized as effective rainfall events with an infiltration depth exceeding 10 cm, accounting for only 11.6% of the total. In this study, the temporal distribution of rainfall was classified into four types: transitory, constant, unimodal, and multimodal. Analysis of the monitoring data showed that transitory rainfall events were all effective, constant rainfall events were mostly effective (> 76%), unimodal rainfall events were 86.7% effective, and all multimodal rainfall events were effective, with the deepest infiltration depth. A three-step method was employed to establish thresholds for different types of rainfall. Firstly, cumulative rainfall exceeding 34 mm at a single time point was considered the most effective rainfall. Secondly, multimodal or constant rainfall with a constant value of Ac > 3.5 mm/3 h and a peak value of Ap > 9.5 mm/3 h was deemed the most effective rainfall. Lastly, a temperature difference Tr during rainfall below 7.7 °C was indicative of mostly ineffective rainfall. The model demonstrated an accuracy of 96%, as validated by existing monitoring data in the nearby loess area. This model has been demonstrated to be superior to previous model and is currently suitable for application in loess regions of China.

Research on Drought Monitoring Based on Deep Learning: A Case Study of the Huang-Huai-Hai Region in China

As climate change intensifies, drought has become a major global engineering and environmental challenge. In critical areas such as agricultural production, accurate drought monitoring is vital for the sustainable development of regional agriculture. Currently, despite extensive use of traditional meteorological stations and remote sensing methods, these approaches have proven to be inadequate in capturing the full extent of drought information and adequately reflecting spatial characteristics. Therefore, to improve the accuracy of drought forecasts and achieve predictions across extensive areas, this paper employs deep learning models, specifically introducing an attention-weighted long short-term memory network model (AW-LSTM), constructs a composite drought monitoring index (CDMI) and validates the model. Results show that: (1) The AW-LSTM model significantly outperforms traditional long short-term memory (LSTM), support vector machine (SVM) and artificial neural network (ANN) models in drought monitoring, offering not only better applicability in meteorological and agricultural drought monitoring but also the ability to accurately predict drought events one month in advance compared to machine learning models, providing a new method for precise and comprehensive regional drought assessment. (2) The Huang-Huai-Hai Plain has shown significant regional variations in drought conditions across different years and months, with the drought situation gradually worsening in the northern part of Hebei Province, Beijing, Tianjin, the southern part of Huai North and the central part of Henan Province from 2001 to 2022, while drought conditions in the northern part of Huai North, southern Shandong Province, western Henan Province and southwestern Hebei Province have been alleviated. (3) During the sowing (June) and harvesting (September) periods for summer maize, the likelihood of drought occurrences is higher, necessitating flexible adjustments to agricultural production strategies to adapt to varying drought conditions.

Bispectral Index Monitoring in the Nursing of Patients With Paroxysmal Sympathetic Hyperactivity.

To investigate the clinical nursing effect of bispectral index (BIS) monitoring for paroxysmal sympathetic hyperactivity (PSH) patients in the neurosurgical intensive care unit (NICU). From January 2022 to June 2023, a total of 30 patients with PSH secondary to moderate to severe craniocerebral injury in the NICU were monitored for BIS. The patients' paroxysmal sympathetic hyperactivity-assessment measure (PSH-AM) scores were recorded. PSH patients generally appear in 3 states: calm state, seizure state, and postmedication state. Thirty PSH patients' BIS values were recorded during the calm period, during the seizure state, and postmedication state, and these 3 different stages' BIS values were divided into groups A, B, and C, using the Kruskal-Wallis H test to compare groups. The Kruskal-Wallis H test yielded a value of H=22.599, P <0.001. H0 was rejected against the test standard of α=0.05, and the BIS values of groups A, B, and C differed. The BIS values of group A and group B differed after a pairwise comparison, and the difference was statistically significant (adjusted P =0.001). Group B and group C had different BIS values, and the difference was statistically significant (adjusted P =0.001); group A and Group C had no difference in BIS values, and the difference was not statistically significant (adjusted P =1.00). Taking BIS value as the nursing observation index for PSH patients can make nursing work more objective, reasonable, and accurate, reduce the inducing factors of PSH attack, further reduce the attack of PSH, save nursing resources, and help guide the safety assessment of sedative use.

Vitamin D3 improves glucose metabolism and attenuates inflammation in prediabetic human and mice

Prediabetes is a crucial stage for prevention and treatment of diabetes, and vitamin D (VD) has been found to be linked to the development of prediabetes and diabetes. Thus, we aimed to identify the effect of VD supplementation on glucose metabolism in prediabetic participants and mice. A 1:1 paired design of randomized, placebo-controlled trial with 1600 IU/day VD3 or placebo was administered to individuals with prediabetes, two-way repeated-measures ANCOVA was used to analyze glycolipid and inflammatory factors. A high-fat diet induced prediabetic KKay mice were utilized to evaluate the effects of VD3 with 16 weeks supplementation. Generalized estimation equation, one way ANOVA were used to analyze continuous monitoring indexes and terminal indexes, respectively. Exercise capacity, skeletal muscle pathological features and relevant proteins were examined. The clinical results showed that VD3 could improve insulin secretion and decrease inflammation. Results of KKay mice exhibited that VD3 not only ameliorate glycolipid metabolism and inflammatory indicators, but also regulated pathological changes of skeletal muscle and exercise capacity. Mechanistically, our results demonstrated that VD3 could inhibit the TLR4/NFκB and activate PI3K/AKT signaling pathway. Collectively, the study indicated that VD3 exerts its beneficial effects by inhibiting TLR4/NFκB to decrease inflammatory response, and activating PI3K/AKT signaling pathway to regulate glucose homeostasis.

A Hybrid Index for Monitoring Burned Vegetation by Combining Image Texture Features with Vegetation Indices

The detection and monitoring of burned areas is crucial for vegetation recovery, loss assessment, and anomaly analysis. Although vegetation indices (VIs) have been widely used, accurate vegetation detection is challenging due to potential confusion in the spectra of different types of land cover and the interference of shadow effects caused by terrain. In this work, a novel Vegetation Anomaly Spectral Texture Index (VASTI) is proposed, which leverages the merits of both spectral and spatial texture features to identify abnormal pixels for extracting burned vegetation areas. The performance of the VASTI and its components, the Global Environmental Monitoring Index (GEMI), the Enhanced Vegetation Index (EVI), and the texture feature Autocorrelation (AC) were assessed based on a global dataset previously established, which contains 1774 pairs of samples from 10 different sites. The results illustrated that, compared with the GEMI and EVI, the VASTI improved the user’s accuracy (UA), producer’s accuracy (PA), and kappa coefficient across the ten study areas by approximately 5% to 10%. Compared to AC, the VASTI improved the accuracy of abnormal vegetation detection by 13% to 25%. The improvements were mainly caused by the fact that the incorporation of texture features can reduce spectral confusion between pixels. The innovation of the VASTI is that it considers the relationship between anomalous pixels and surrounding pixels by explicitly integrating spatial texture features with traditional spectral features.

Intraoperative transcutaneous electroacupoint stimulation on early postoperative fatigue in patients with Parkinson's disease undergoing deep brain stimulation surgery

BackgroundIn this clinical trial, we evaluated the effects of transcutaneous electroacupoint stimulation (TEAS) on postoperative fatigue (POF) in Parkinson disease (PD) patients undergoing deep brain stimulation (DBS) surgery. MethodsA total 60 PD patients undergoing DBS surgery were enrolled. They were randomized to receive either electrical stimulation [alternative frequency 2/10 Hz, dense and disperse, intensity adjusted to the maximum tolerated by the participants (6–15 mAmp)] via surface electrodes (TEAS group) or surface electrodes only without electrical stimulation (Con group) at bilateral Zusanli and Sanyinjiao acupuncture points. All participants received their assigned intervention (TEAS or Con) during the 1st stage of surgery [(except during microelectrode recording (MER)] and the entire 2nd stage of surgery. Intraoperative anesthetic requirements were adjusted based on bispectral index (BIS) monitor. POF was assessed by Christensen fatigue scales (ChrFS), along with Quality of Recovery-15 (QoR-15) and mini-mental state examination (MMSE) postoperatively over a 7-day-period. We recorded the usage of rescue analgesics and anti-emetics. ResultsFifty-nine patients’ datasets were included for final analyses. Fewer patients in TEAS experienced severe POF (defined as ChrFS ≥6) at T3 than those in the Con group (TEAS vs. Con: 7 vs. 22, p < 0.001). During the 1st stage of surgery, more patients in Con group required dexmedetomidine infusion (TEAS vs. Con: 2 vs. 6; P < 0.01). Total dosages of propofol and remifanil during the 2nd stage of surgery were TEAS vs. Con: 374.7 ± 61.2 vs 421.5 ± 81.9; p < 0.001 and 572.3 ± 82.0 vs. 662 ± 148.2; P < 0.001, respectively. Postoperative rescue analgesics (TEAS vs. Con: 2 vs. 6; P < 0.001) were used less in the TEAS group. TEAS patients reported better POF, MMSE and QoR15 scores than those in the Con group during most of the assessment period. ConclusionsIntraoperative TEAS decreased the severity of POF, reduced intraoperative anesthetic requirements and facilitated post-DBS recovery in this group of PD patients.

The effect of propofol-midazolam versus sevoflurane on bispectral index and eye position in pediatric cataract surgery: A randomized controlled study

ABSTRACT Background Cataract surgery is one of the infrequent ocular surgeries. The adequate ocular position with central alignment is the main prerequisite for good surgical technique. Propofol and sevoflurane are the common anesthetics drugs used during pediatric anesthesia. BIS monitor is one of the common intraoperative awareness monitors used. Aim To assess the efficacy of the bispectral index monitor in quantifying the depth of anesthesia and its correlation with ocular alignment during juvenile cataract surgery. Specifically, we will compare the use of sevoflurane anaesthesia with total intravenous anesthesia using a midazolam bolus and propofol infusion. Methods This study included 100 children scheduled for cataract surgery. The children were divided into two groups: group (S) included 50 children who were anesthetized using sevoflurane maintenance only and group (P) included 50 children who were anesthetized using continuous intravenous anesthesia (midazolam bolus plus propofol infusion) as maintenance after induction with sevoflurane anesthesia 8%. The bispectral index was recorded immediately after induction and after intubation and every 5 min later on until end of surgery. Results The eye position showed statistically significant central position among the propofol group with p value 0.02. An eye position-BIS value association was found statistically significant negative correlation in sevoflurane group while no statistically significant link was found in the propofol group. Conclusion Use of BIS monitor for making correlation between depth of anesthesia for prediction of ocular alignment was significant in sevoflurane group, but not in propofol group in pediatric patients and even with adequate depth of general anesthesia.

Effect of starch granule size on the properties of dough and the oil absorption of fried potato crisps

Starch is a key element in fried potato crisps, however, the effect of starch granule size on oil absorption of the product have yet to be fully investigated. The study explored the impact of starch granule size on both the dough characteristics and oil absorption in potato crisps. The dough composed of small-sized potato granules showed more compact and uniform network system. Additionally, X-ray Microscope analysis showed that potato crisps prepared with small-sized potato granules had limited matrix expansion and fewer pores, cracks, and voids. The small-sized potato and small-sized wheat starches granule addition crisps displayed a significantly greater average cell thickness (52.05 and 53.44 μm) than other samples, while exhibiting notably lower average porosity (61.37 % and 60.28 %) compared to other samples. Results revealed that potato crisps with medium and small potato granules had 12.91 % and 21.92 % lower oil content than those containing large potato starch. Potato crisps with B-type wheat starch showed 16.36 % less oil absorption than those with A-type wheat starch. Small-sized starches significantly influence the dough structure and contribute to the reduction of oil absorption in fried products. The generated insights may provide monitoring indexes for cultivating potato varieties with low oil absorption.

Harnessing the power of artificial intelligence: A new door for quick surgery in Pakistan.

Artificial intelligence (AI) has the potential to transform surgery in Pakistan, improving results, reducing complications, and increasing patient safety. Deep learning, a branch of machine learning, can assist surgeons in making wise judgments. Pubmed and Research Gate discuss the promise of AI in surgery. Incorporating AI in healthcare systems can expedite diagnosis and management while avoiding injudicious resource allocation. AI-based techniques in cardiology, nephrology, and neurology enable high-accuracy detection of cardiovascular disease risks, kidney disease treatment, and epileptic episode identification. Neurological devices like bispectral index monitor (BIS) and Near-infrared spectroscopy (NIRS) utilize advanced technology for reliable monitoring and objective diagnosis of neurological issues (Ahmed, 2022). AI uses electronic data and neural network methods to evaluate operating room logistics, time management, and anesthesiologist activities using electronic data and neural network methods (Khan F. H., 2019). AI algorithms are effectively detect minute differences for accurate diagnosis, with studies showing high specificity, sensitivity, and inter-operator repeatability. AI can be used to train and assess neurosurgical residents and early mid-career surgeons, improving diagnosis and 3D simulation labs (Shlobin, 2022). Surgeons play a crucial role in adopting AI-based technologies for surgical care by partnering with data scientists to capture novel clinical data and generate meaningful interpretations. They should demand transparency and interpretability in algorithms to hold AI accountable for its predictions and recommendations.AI advancements in plastic surgery practice, research, and education offer opportunities for improvement. Combining AI-enabled decision-making tools with predictive analytics and human intuition, surgeons can make real-time decisions based on 3D planning, anatomical localization, and navigation (Rasteau, 2022). While current AI tools cannot perform complex surgical procedures, advancements may enable them to perform more complex tasks in the future. Pakistan is a significant market for AI-based solutions, utilizing technology in various industries to address challenges and boost demand. The country has enhanced its self-security systems, including AI-powered missiles, cyber security, and effective cameras (Khan, 2022). AI allows tasks to be completed more precisely and efficiently, with machine learning and deep learning being advanced subtypes. In developing countries like Pakistan, AI tools are needed for patient-centred diagnosis and treatment assistance, especially in emergency surgery such as cardiac illnesses or life threatening bleeding caused road traffic accident. Hence insuring patient receive care timely. An appropriate budget should be allocated for AI technologies in the health sector.

Correlation between serum leptin level and sleep monitoring indexes in patients with obstructive sleep apnea hypopnea syndrome and its predictive value: a cross-sectional analysis.

To investigate the association between serum leptin (LP) level and polysomnography (PSG) parameters in patients with obstructive sleep apnea hypopnea syndrome (OSAHS). A cross-sectional study was conducted. The data of subjects who underwent PSG at hospital between January 2021 and December 2022 were collected retrospectively, 220 participants were included. The subjects were categorized into simple snoring group (n = 45), mild OSAHS group (n = 63), moderate OSAHS group (n = 52), and severe OSAHS group (n = 60). The general characteristics, PSG indices, and serological indices were collected retrospectively. Pearson correlation analysis was used to observe the correlation between serum LP level and PSG parameters. The value of serum LP level in predicting OSAHS was analyzed by receiver operating characteristic curve. The serum LP level was positively correlated with micro-arousal count, micro-arousal index (MAI), high apnea hypopnea index, times of blood oxygen decreased by≥3% and time in saturation lower 90%, and negatively correlated with lowest nocturnal oxygen saturation and mean oxygen saturation (p < 0.05). The area under the curve (AUC) of serum LP level in predicting the occurrence of OSAHS was 0.8276 (95% CI: 0.7713-0.8839), and when the Youden index was 0.587, the sensitivity was 72.00%, and the specificity was 86.67% (p < 0.0001). In the population with high MAI, the AUC of serum LP level in predicting the occurrence of OSAHS was 0.8825 (95% CI: 0.7833-0.9817), and when the Youden index was 0.690, the sensitivity was 79.00% and the specificity was 90.00% (p < 0.0001). Serum LP level is associated with the severity of OSAHS. Serum LP level demonstrates a strong predictive value for the occurrence of OSAHS, particularly in population with high MAI.

Assessment of compaction quality of highway subgrade via roller-integrated positive maximum velocity detection technique

ABSTRACT Quality control of compaction is vital for the long-term performance of highways. Specifically, the assessment of subgrade compaction quality is a key factor. Currently, compaction quality is primarily controlled by parameters set during compaction and subsequent random sampling tests post-construction. However, the impact of human factors and limitations of these sampling tests fall short of meeting the standards of large-scale precision construction. This study introduces a real-time monitoring index to characterise the compaction quality of silt subgrades: the maximum velocity compaction value (MVCV). This index is derived using a combination of the roller-integrated positive maximum velocity detection system and real-time kinematic Beidou positioning system (RTK-BDS). Furthermore, the Green spline interpolation method allows for estimating compaction quality values at any point. A case study from the Hengyong Highway project in China reveals a strong linear relationship between compaction parameters and compactness. This suggests the suitability of this method for characterising the compaction quality of such silt. This assessment approach facilitates a detailed evaluation of compaction quality across the entire construction zone. Hence, it aids in effectively minimising compaction defects, reducing unnecessary rework, and enhancing the overall compaction quality and efficiency of highway construction.

Data Driven and Fuzzy Synthetic Evaluation Based Submarine Cable Health State Assessment

—Health state assessment is of great importance to ensure the safe and stable operation of submarine cables. Submarine cables have composite structural characteristics and work in complex and influential environments, which hinders manual inspection, arouses difficulties in maintenance, and causes challenges on health state assessment. To this end, a data driven and fuzzy synthetic evaluation based submarine cable health state assessment method is proposed in this paper. Firstly, following the technical guidelines of submarine cable health state assessment, dynamic submarine cable online monitoring data and static data including periodic preventive test and operation inspection results are integrated to build a three-layer index system. In addition, long and short-term memory (LSTM) neural network based ultra-short-term prediction models are built to obtain the predictions of online monitoring indices. On this basis, together with the static data, a fuzzy synthetic evaluation method is used to establish a two-stage state evaluation process to obtain the multi-period health states of submarine cables. The effectiveness of the proposed method is verified with an actual submarine cable from an offshore platform in an oilfield of China National Offshore Oil Corporation (CNOOC).

Role of oxygen reserve index monitoring in patients undergoing robot-assisted radical prostatectomy: a retrospective study

PurposeRobot-assisted radical prostatectomy (RARP) is a common surgical procedure for the treatment of prostate cancer. Although beneficial, it can lead to intraoperative hypoxia due to high-pressure pneumoperitoneum and Trendelenburg position. This study explored the use of oxygen reserve index (ORi) to monitor and predict hypoxia during RARP.MethodsA retrospective analysis was conducted on 329 patients who underwent RARP at the Seoul National University Bundang Hospital between July 2021 and March 2023. Various pre- and intraoperative variables were collected, including ORi values. The relationship between ORi values and hypoxia occurrence was assessed using receiver operating characteristic curves and logistic regression analysis.ResultsIntraoperative hypoxia occurred in 18.8% of the patients. The receiver operating characteristic curve showed a satisfactory area under the curve of 0.762, with the ideal ORi cut-off value for predicting hypoxia set at 0.16. Sensitivity and specificity were 64.5% and 75.7%, respectively. An ORi value of < 0.16 and a higher body mass index were identified as independent risk factors of hypoxia during RARP.ConclusionsORi monitoring provides a non-invasive approach to predict intraoperative hypoxia during RARP, enabling early management. Additionally, the significant relationship between a higher body mass index and hypoxia underscores the importance of individualized patient assessment.

Plasmonic Sensor System Embedded with Orthogonal Mode Couplers for Simultaneous Monitoring of Temperature and Refractive Index

AbstractThe significance of plasmonic sensors lies in their ability to enhance sensitivity and precision in detecting minute variations in the refractive index of surrounding media. In this work, a novel plasmonic sensor design utilizing a metal-insulator-metal (MIM) waveguide and two circular cavities is presented, specifically tailored for refractive index and temperature sensing applications. Each cavity serves as an individual and autonomous sensing unit. Tailored for temperature sensing, a designated cavity is filled with polydimethylsiloxanes (PDMS), while a separate cavity is exclusively allocated for biosensing and contains a liquid with distinct refractive indices. This dual-cavity system allows for precise and specialized sensing functionalities, ensuring accurate measurements and diverse applications. Furthermore, this work integrates orthogonal mode couplers into the plasmonic device, providing an essential capability to seamlessly transform the dielectric mode into a plasmonic mode and vice versa. The device exhibits a refractive index sensitivity of 737.71 nm/RIU and a temperature sensitivity of − 0.336 nm/°C. Additionally, its Q-factor is determined at 20.5 for the refractive index sensing module and 16.5 for the temperature sensing module.

Comparison of different drought monitoring indices in different climatic conditions in Iran

This study evaluates drought in different climate zones (Rasht, Shiraz, and Birjand) in Iran, using meteorological, agricultural, and remote sensing drought indices. For this purpose, NDVI, SAVI, and SR were extracted from Landsat images for 2002 and 2014-2020. Then, these indices were compared with the SPI, SPEI, and PDSI. The results indicate an increase in drought and a decrease in vegetation cover in the study area. In Rasht, where the vegetation cover is high, NDVI and SAVI were equal. In Shiraz and Birjand, where the soil effect is more significant, the distance between these two indices increased, which shows that SAVI performs better than NDVI for Shiraz and Birjand. The results also show that the drought severity could grow with decreasing rainfall and more water demand due to temperature increases, according to SPI, SPEI, and PDSI criteria. The comparison of drought indices showed that the highest correlations were between NDVI plus SAVI and SPI in Rasht, SR and SPEI in Shiraz, and NDVI and SPEI in Birjand. Based on the results of the Mann-Kendall test, the increasing trend of drought in the studied area is confirmed based on the SPI, SPEI, and PDSI. Therefore, it is suggested that remote sensing techniques combined with drought indices can be considered a suitable tool for optimal management of water resources, land use planning, and reduction of costs due to drought.

UAVs for improving seasonal vegetation assessment in arid environments

In the last few decades, revegetation strategies for ecosystem restoration have received great attention in dryland studies, especially those related to the restoration and revegetation of native desert plants to combat land degradation. Long-term monitoring and assessment are critical for the restoration programs to track the progress of the restoration program goals. The effectiveness and success of monitoring depend on the selected methods with respect to spatial and temporal scales. Traditional methods for vegetation monitoring are time-consuming, expensive, and require considerable labor efforts (manpower) in terms of field measurements, collecting samples, lab analysis, and the difficulty of accessing some study areas. Thus, satellite remote sensing images have been widely used to monitor land degradation and restoration programs using multispectral and hyperspectral sensors and indices such as NDVI, which is the most popular index for vegetation monitoring. However, such techniques showed many limitations when used in arid ecosystems, especially for seasonal vegetation assessments, which could mislead the monitoring and assessment of the restoration projects. This paper discusses lessons learned from previous research work, including the limitations of using satellite remote sensing in arid ecosystems and the use of UAV methods to overcome these issues and challenges to provide more accurate outcomes for seasonal assessment of vegetation in arid landscapes.

Comparison of the Effects of Inhalational Anesthesia with Sevoflurane and Total Intravenous Anesthesia in Open Heart Surgery

Background: The primary objective of this study was to compare sevoflurane inhalation anesthesia with total intravenous anesthesia (TIVA) in terms of its effectiveness in maintaining adequate depth of anesthesia during all open heart surgery procedures, including cardiopulmonary bypass. The study's secondary objective was to compare sevoflurane inhalation anesthesia with TIVA regarding the impact on the time of tracheal extubation and the incidence of postoperative acute kidney injury during open heart surgeries. Methods: A total of 58 patients undergoing open heart surgery were included, with 30 receiving sevoflurane inhalation anesthesia and 28 receiving TIVA. Demographic characteristics, intraoperative parameters, and postoperative outcomes were recorded and analyzed. Statistical analysis revealed no significant differences in Bispectral Index (BIS) monitor values, mean arterial pressure, body temperature, or other intraoperative parameters between the two groups. Notably, the time to tracheal extubation was significantly shorter in the Sevoflurane group compared to the TIVA group, although both groups exhibited similar rates of postoperative acute kidney injury (AKI). Results: None of the patients had complaints of intraoperative awareness. The mean arterial pressure, body temperature, and bispectral index values during and before cardiopulmonary bypass were similar between the groups. Postoperative variables such as intensive care unit stay duration, incidence of acute kidney injury, and immediate and 24-hour post-extubation visual analog scale values were similar between the groups. The tracheal extubation time was found to be statistically shorter in the sevoflurane group. Conclusion: We believe that sevoflurane inhalation anesthesia can achieve adequate depth of anesthesia during the intraoperative period in open heart surgery without increasing the rate of postoperative complications.

Comparison of Hemodynamic Effects of Dose Response vs. Conventional Dosing of Propofol for Anesthesia Induction Under Bispectral Index Monitoring: A Clinical Trial

Propofol is an advantageous agent for anesthesia induction. It can cause dose-related hemodynamic adverse effects. The bispectral index (BIS) is a brain function monitor utilized to assess the depth of anesthesia. This study aimed to compare the adverse hemodynamic effects of BIS-guided response dosing with conventional weight-based dosing of Propofol. In this clinical trial, patients were anesthetized with propofol in two different orthopedic operating rooms. In one operating room, patients received propofol with dose-response method (group A), and the other received weight-based dosing (group B). For both groups, BIS was used as an index of anesthesia depth. Hemodynamic parameters were recorded at baseline, during induction, and at different time points. A total of 73 patients were included in the final analysis. The mean dose of propofol for induction was higher in the control group than in the response-guided group (1.94±1.65 vs. 1.09±0.32, respectively, P=0.006). There were no reported significant adverse hemodynamic effects in patients of the two groups. Response-guided propofol dosing can be used to decrease propofol dose during anesthesia induction. Further studies are needed to investigate the clinical benefit of this dosing strategy.

Bispectral index monitoring for sedation in scheduled adult colonoscopy: A randomized controlled trial

BackgroundPatients should be closely monitored during procedures under sedation outside the operating room, but it is unclear which type of monitoring is best. We investigated the efficacy and safety of BIS monitoring vs conventional monitoring for sedation during colonoscopy. MethodsWe performed a double-blind clinical trial in 180 patients undergoing elective colonoscopy. Patients were randomized to 1) the BIS group or 2) a control group, in which sedation was monitored with a BIS monitor or the Ramsay Sedation Score, respectively. The primary outcome was the rate of sedation-induced adverse events in both groups. Secondary outcomes were the characteristics of patients who developed adverse events, and time during colonoscopy when these events occurred, propofol and remifentanil dosage, and patient satisfaction. ResultsUnivariate analysis showed fewer cardiopulmonary complications in the BIS group (41.11% vs 57.78% in controls; p = 0.02). Multivariate analysis found a significantly higher risk of adverse events in older patients (95% CI, 1.013–1.091; p = 0.0087) and in men (95% CI, 1.129–7.668; p = 0.0272). These events were observed at the hepatic flexure. No significant differences between propofol or remifentanil dosage, use of rescue medication, and patient satisfaction were observed between groups. ConclusionsOur data suggest that BIS monitoring during sedation in scheduled colonoscopies reduces adverse respiratory events. Although its routine use in sedation does not appear to be warranted, clinicians should take steps to identify patients with a higher risk of complications who might benefit from this type of monitoring.