Essential Parameters Research Articles

Effect of junction temperature on 1.3 µm InAs/GaAs quantum dot lasers directly grown on silicon

Laser junction temperature (Tj) is an essential parameter that directly affects the light power and lifetime of semiconductor lasers. Here, we investigate the effect of Tj on an InAs/GaAs quantum dot (QD) laser grown on a Si(001) substrate. Under 1% low pulsed current (1 µs pulse width and 100 µs period), the pure temperature-induced mode shift rate is 0.084 nm/°C. By increasing the duty cycle and measuring the corresponding mode wavelength shift, the laser’s Tj under the continuous-wave (Tj-CW) mode is predicted to be from 31.1 to 81.6 °C when the injection current increases from 100 to 550 mA. Next, the average thermal resistance is 36.2 °C/W. Moreover, the non-negligible increase in Tj-CW is analyzed to significantly reduce the mean-time-to-failure of Si-based QD laser, especially for cases under high CW injection currents. These results provide an accurate reference for the thermal analysis of silicon-based QD lasers and point the way to high performance on-chip light sources by improving the laser heat accumulation.

WHaD diagram: Classifying the ionizing source with one single emission line

Context. The usual approach to classify the ionizing source using optical spectroscopy is based on the use of diagnostic diagrams that compare the relative strength of pairs of collisitional metallic lines (e.g., [O III] and [N II]) to recombination hydrogen lines (e.g., Hβ and Hα). Despite it having been accepted as the standard procedure, it presents known problems, including confusion regimes and/or limitations related to the required signal-to-noise (S/N) of the emission lines involved. These problems not only affect our intrinsic understanding of the interstellar medium and its properties, but also the fundamental galaxy properties, such as the star formation rate and the oxygen abundance. This raises key questions related to the fraction of active galactic nuclei and other essential parameters. Aims. We attempt to minimize the problems introduced by the use of these diagrams, in particular, their implementation when the available information is limited due to either the fact that not all lines are available or they do not have the required S/N value. Methods. We explored the existing alternatives in the literature to minimize the confusion among different ionizing sources. We have proposed a new, simple diagram that uses the equivalent width and the velocity dispersion from one single emission line, Hα, to classify the ionizing sources. Results. We used aperture-limited and spatially resolved spectroscopic data from the nearby Universe (z ∼ 0.01) to demonstrate that the new diagram, which we have named WHaD, segregates the different ionizing sources in a more efficient way than earlier procedures. A new set of regions have been defined in this diagram to select among different ionizing sources. Conclusions. The new proposed diagram is well positioned to assist in determining the ionizing source when only Hα is available or when the S/N of the emission lines is too low to obtain reliable fluxes for the weakest emission lines in classical diagnostic diagrams (e.g., Hβ).

A Generalized Kinetic Model of Fractional Order Transport Dynamics with Transit Time Heterogeneity in Microvascular Space.

The aim of this study is to develop and validate a unifying kinetic model for microvascular transport by introducing an impulse response function that incorporates essential physiological parameters and integrates key features of existing models. This new methodology combines a one-compartment model of fractional order with a model that uses the gamma distribution to describe the distribution of capillary transit times. Central to this model are two primary parameters: [Formula: see text], representing the kurtosis of residue times, and [Formula: see text], signifying the width of the distribution of capillary transit times within a tissue voxel. To validate this proposed model, data from dynamic contrast-enhanced magnetic resonance imaging (DCI-MRI) were employed and the findings were compared with three existing models. Using the Akaike information criterion for model selection, the results demonstrate that the integrative model, especially at elevated blood flow rates, frequently offers superior fits in comparison to constrained models.

Strong Association of Metabolic Parameters with ADMA and VCAM-1 in Normo-Weight Subjects with Metabolic Syndrome.

Metabolic syndrome (MetS) is a risk factor for cardiovascular disease and is linked to obesity. Subjects with MetS who have normo-weight potentially show higher mortality and morbidity. This study aims to reveal the critical essential metabolic parameters associated with endothelial dysfunction in MetS subjects with normo-weight compared to obese. The study was designed using a case-control approach. Ninety-nine MetS subjects (34 Normo-weight and 65 obese) from the urban population were enrolled in this study. The components of MetS are based on NCEP/ATP III criteria. Asymmetric dimethylarginine (ADMA) and vascular cell adhesion molecule 1 (VCAM-1) as markers for endothelial dysfunction were measured in both groups. Fasting blood glucose (FBG) levels were higher in the normo-weight group (143.38 ± 79.8 mg/dL) compared to the obese group (120.89 ± 46.5 mg/dL). High-density lipoprotein cholesterol (HDL-c) levels in the normo-weight group were lower (42.82 ± 10.1 mg/dL) compared to obesity (45.74 ± 9.3 mg/dL), while triacylglycerol (TAG) levels were higher in the obese (197.25 ± 110.5 mg/dL) compared to the normo-weight group (167.03 ± 98.4 mg/dL), although the differences were statistically not significant (all p > 0.05). The difference between ADMA and VCAM-1 levels was statistically not significant in both groups. Correlation between MetS components with endothelial dysfunction parameters shows that metabolic parameters correlate strongly. Interestingly, a stronger correlation between FBG and ADMA was observed in normo-weight (r = 0.519) compared to obese groups (r = 0.445). In addition, TAG consistently shows a significant correlation with ADMA and VCAM-1 in normo-weight groups. Metabolic parameters, especially FBG and TAG, correlate strongly with endothelial dysfunction parameters in normo-weight subjects with metabolic syndrome.

On the physical meaning of the geometric factor and the effective thickness in the Montgomery method

The Montgomery method is extensively employed to determine the electrical resistance tensor of anisotropic samples. This technique relies on two essential parameters describing an isotropic system: the geometric factor (H1) and the effective thickness (E). The numerical values of these parameters are intricately linked to the dimensions of an isotropic block equivalent to the studied anisotropic specimen. While these parameters hold importance, the physical interpretation of these terms still lacks clarity. In this study, we utilized the finite element method to simulate electrical transport experiments across samples of various shapes. Utilizing the Electric Currents physics interface in the COMSOL program, we were able to provide a comprehensive analysis of the physical meaning of these parameters to accurately determine the electrical properties of thin films and wafers. The presented findings related to the physical interpretation of H1 and E terms make substantial contributions to the field of electrical transport experimental techniques, which are fundamental to design advanced materials for technological applications and understand their physical properties.

Investigation and establishment of rational geometric factors of die in the deep drawing without a blank holder

Deep drawing is an operation to transform flat or hollow blanks to create hollow parts of the required shape and size. Deep drawing is an essential operation in sheet-forming technology to manufacture hollow parts. These parts are commonly used in the automobile, aviation, and household appliances industries. To prevent wrinkles on the rim part, a blank holder will be used to compress and flatten the workpiece before the metal is pulled into the die by the punch. Deep drawing without using workpiece holding force is applied to form hollow parts with low depth. In this case, the mould has a simple structure, helping to reduce manufacturing time and costs and making it easier to maintain and repair. The radius of the die is an essential parameter in deep drawing; it greatly affects the quality of products (making wrinkles and tears). However, this study has shown that, in deep drawing without using a blank holder, the cone angle of the die α has a major influence on the quality of the body and rim of the products, such as the products may or may not have wrinkles, either being thinned or thickened. This cone angle also affects the drawing force. This study has determined that, with α>120°, wrinkling begins to appear in the part wall, and wrinkling tends to increase as the angle α increases. The cone angle of the die for quality products is in the range of 100°<α≤120°. The taper angle smaller than 120° simultaneously increases the quality of the products and the cost of manufacturing die, so the most optimal value is determined by simulation and experimental verification as α=120°. The results of this study can be applied to fabricate hollow cylindrical parts with similar shapes when using the deep drawing method without using the blank holder

Full-Scale Experimental and Field Investigations into Expansion Mechanism of Foamed Polyurethane and its Lifting Behaviors for Repair and Maintenance of Railway Slab Track Systems.

Excessive settlement of the subgrade seriously reduces the service quality of slab tracks and threatens trains' running safety. While the utilization of foamed polyurethane is recognized as an effective solution, previous research on its expansion mechanism and its impact on track lifting requires further refinement. Accordingly, a series of full-scale tests, including expansion force tests on foamed polyurethane with diverse qualities and lifting tests of polyurethane grouting with varied qualities on the track structure, have been conducted. The expansion development process of foamed polyurethane is meticulously elucidated, and key expansion parameters are analyzed. Simultaneously, this research explores the lifting behavior of foamed polyurethane grouting under the slab tracks, yielding new insights into essential lifting parameters for track formation repair and maintenance. Based on the experimental data, this study proposes new empirical formulas to comprehensively describe both the expansion mechanism of foam polyurethane and its lifting behavior under the slab tracks. The outcomes of this research offer a new breakthrough for the design of lifting mechanism for maintaining slab track structures through the utilization of foam polyurethane slurry grouting, such as determining the optimal grouting quantity. In addition, these results are instrumental to the evaluation of lifting effects and service life, enhancing the circular economy of railway track systems.

Minimum Information for Conducting and Reporting In Vitro Intracellular Infection Assays.

Bacterial pathogens are constantly evolving to outsmart the host immune system and antibiotics developed to eradicate them. One key strategy involves the ability of bacteria to survive and replicate within host cells, thereby causing intracellular infections. To address this unmet clinical need, researchers are adopting new approaches, such as the development of novel molecules that can penetrate host cells, thus exerting their antimicrobial activity intracellularly, or repurposing existing antibiotics using nanocarriers (i.e., nanoantibiotics) for site-specific delivery. However, inconsistency in information reported across published studies makes it challenging for scientific comparison and judgment of experiments for future direction by researchers. Together with the lack of reproducibility of experiments, these inconsistencies limit the translation of experimental results beyond pre-clinical evaluation. Minimum information guidelines have been instrumental in addressing such challenges in other fields of biomedical research. Guidelines and recommendations provided herein have been designed for researchers as essential parameters to be disclosed when publishing their methodology and results, divided into four main categories: (i) experimental design, (ii) establishing an in vitro model, (iii) assessment of efficacy of novel therapeutics, and (iv) statistical assessment. These guidelines have been designed with the intention to improve the reproducibility and rigor of future studies while enabling quantitative comparisons of published studies, ultimately facilitating translation of emerging antimicrobial technologies into clinically viable therapies that safely and effectively treat intracellular infections.

Automated deep learning model for estimating intraoperative blood loss using gauze images

The intraoperative estimated blood loss (EBL), an essential parameter for perioperative management, has been evaluated by manually weighing blood in gauze and suction bottles, a process both time-consuming and labor-intensive. As the novel EBL prediction platform, we developed an automated deep learning EBL prediction model, utilizing the patch-wise crumpled state (P-W CS) of gauze images with texture analysis. The proposed algorithm was developed using animal data obtained from a porcine experiment and validated on human intraoperative data prospectively collected from 102 laparoscopic gastric cancer surgeries. The EBL prediction model involves gauze area detection and subsequent EBL regression based on the detected areas, with each stage optimized through comparative model performance evaluations. The selected gauze detection model demonstrated a sensitivity of 96.5% and a specificity of 98.0%. Based on this detection model, the performance of EBL regression stage models was compared. Comparative evaluations revealed that our P-W CS-based model outperforms others, including one reliant on convolutional neural networks and another analyzing the gauze’s overall crumpled state. The P-W CS-based model achieved a mean absolute error (MAE) of 0.25 g and a mean absolute percentage error (MAPE) of 7.26% in EBL regression. Additionally, per-patient assessment yielded an MAE of 0.58 g, indicating errors < 1 g/patient. In conclusion, our algorithm provides an objective standard and streamlined approach for EBL estimation during surgery without the need for perioperative approximation and additional tasks by humans. The robust performance of the model across varied surgical conditions emphasizes its clinical potential for real-world application.

The 28S rRNA RT-qPCR assay for host depletion evaluation to enhance avian virus detection in Illumina and Nanopore sequencing.

Abundant host and bacterial sequences can obscure the detection of less prevalent viruses in untargeted next-generation sequencing (NGS). Efficient removal of these non-targeted sequences is vital for accurate viral detection. This study presents a novel 28S ribosomal RNA (rRNA) RT-qPCR assay designed to assess the efficiency of avian rRNA depletion before conducting costly NGS for the detection of avian RNA viruses. The comprehensive evaluation of this 28S-test focuses on substituting DNase I with alternative DNases in our established depletion protocols and finetuning essential parameters for reliable host rRNA depletion. To validate the effectiveness of the 28S-test, we compared its performance with NGS results obtained from both Illumina and Nanopore sequencing platforms. This evaluation utilized swab samples from chickens infected with highly pathogenic avian influenza virus, subjected to established and modified depletion protocols. Both methods significantly reduced host rRNA levels, but using the alternative DNase had superior performance. Additionally, utilizing the 28S-test, we explored cost- and time-effective strategies, such as reduced probe concentrations and other alternative DNase usage, assessed the impact of filtration pre-treatment, and evaluated various experimental parameters to further optimize the depletion protocol. Our findings underscore the value of the 28S-test in optimizing depletion methods for advancing improvements in avian disease research through NGS.

Instant Granule Formulation Combining White Sweet Potato Leaves Extract (Ipomoea batatas (L.) Lam.) and Javanese Chili (Piper retrofractum Vahl)

Dengue haemorrhagic fever is a viral infection transmitted by the Aedes aegypti mosquito, which is one of the symptoms is thrombocytopenia. The extract from white sweet potato leaves is recognized for its potential to increase the number of platelet count. This research aimed to develop a formula for an instant granule combining white sweet potato leaves extract with Javanese chili extract meeting taste preferences and societal acceptability. The preparation of the extract was performed by maseration using 70% ethanol and then concentrated with a rotary evaporator. The result was a thick extract which was then dried in an oven at 50℃. The manufacture of instant granule formulations was conducted using wet granulation method. Various formulations were obtained by differentiated concentration of Javanese chili used in the formula (FI 1%, FII 2%, and FIII 3%). The instant granule formulation was evaluated by organoleptic assay and other essential parameters for instant granule, such as moisture content, flow rate, angle of repose, and particle size distribution. The FII 2% formulation emerged as the most acceptable with an average score of 2.17. Non-parametric analysis indicated no significant difference among the three formulas, as the obtained significant value (α) was ≥ 0.05, leading to the acceptance of the null hypothesis H0.

Added value of ratio of cross diameters of the appendix in ultrasound diagnosis of acute appendicitis.

The maximum outer diameter (MOD) of the appendix is an essential parameter for diagnosing acute appendicitis, but there is space for improvement in ultrasound (US) diagnostic performance. To investigate whether combining the ratio of the cross diameters (RATIO) of the appendix with MOD of the appendix can enhance the diagnostic performance of acute appendicitis. A retrospective study was conducted, and medical records of 233 patients with acute appendicitis and 112 patients with a normal appendix were reviewed. The MOD and RATIO of the appendix were calculated and tested for their diagnostic performance of acute appendicitis, both individually and in combination. The RATIO for a normal appendix was 1.32 ± 0.16, while for acute appendicitis it was 1.09 ± 0.07. The cut-off value for RATIO was determined to be ≤ 1.18. The area under the receiver operating characteristic curve (AUC) for diagnosing acute appendicitis using RATIO ≤ 1.18 and MOD > 6 mm was 0.870 and 0.652, respectively. There was a significant difference in AUC between RATIO ≤ 1.18 and MOD > 6 mm (P < 0.0001). When comparing the combination of RATIO ≤ 1.18 and MOD > 6 mm with MOD > 6 mm alone, the combination showed increased specificity, positive predictive value (PPV), and AUC. However, the sensitivity and negative predictive value decreased. Combining RATIO of the appendix ≤ 1.18 and MOD > 6 mm can significantly improve the specificity, PPV, and AUC in the US diagnosis of acute appendicitis.

Effects of Photoperiod on Survival, Growth, Physiological, and Biochemical Indices of Redclaw Crayfish (Cherax quadricarinatus) Juveniles

Through a 30-day experiment, this study investigated the effects of five photoperiods (0L:24D, 6L:18D, 12L:12D, 18L:6D, and 24L:0D) on the survival, enzyme activity, body color, and growth-related gene expression of redclaw crayfish (Cherax quadricarinatus) juveniles. The results showed that C. quadricarinatus juveniles under 18L:6D and 24L:0D photoperiods exhibited the highest survival rate, which was significantly higher than the survival rates of juveniles under the other three photoperiods (p &lt; 0.05). However, the 0L:24D group had the highest final body weight and weight gain rate, significantly surpassing those of the 12L:12D, 18L:6D, and 24L:0D groups (p &lt; 0.05). Regarding enzyme activity and hormone levels, juveniles under the 18L:6D photoperiod exhibited relatively higher activity of superoxide dismutase (SOD), acid phosphatase (ACP), and lysozyme (LZM) enzymes than those under other photoperiods, but their levels of melatonin and cortisol were relatively low. In addition, the 24L:0D group showed the highest malondialdehyde (MDA) content. Analysis of gene expression levels revealed that retinoid X receptor (RXR) and α-amylase (α-AMY) genes in C. quadricarinatus juveniles exhibited significantly higher expression levels under the 18L:6D photoperiod than those under the other four photoperiods (p &lt; 0.05). With increasing daylight exposure, the body color of C. quadricarinatus changed from pale blue to yellow–brown. In summary, C. quadricarinatus juveniles achieved high survival rates, good growth performance, strong antioxidant stress response, and immune defense capabilities under an 18 h photoperiod. Therefore, in the industrial seedling cultivation of redclaw crayfish, it is recommended to provide 18 h of daily light. Further, the study demonstrated the ability to manipulate the body color of C. quadricarinatus through controlled artificial photoperiods. These findings provide essential technical parameters needed for the industrial cultivation of C. quadricarinatus juveniles.

Essential parameters needed for a U-Net-based segmentation of individual bones on planning CT images in the head and neck region using limited datasets for radiotherapy application.

Objective.The field of radiotherapy is highly marked by the lack of datasets even with the availability of public datasets. Our study uses a very limited dataset to provide insights on essential parameters needed to automatically and accurately segment individual bones on planning CT images of head and neck cancer patients.Approach.The study was conducted using 30 planning CT images of real patients acquired from 5 different cohorts. 15 cases from 4 cohorts were randomly selected as training and validation datasets while the remaining were used as test datasets. Four experimental sets were formulated to explore parameters such as background patch reduction, class-dependent augmentation and incorporation of a weight map on the loss function.Main results.Our best experimental scenario resulted in a mean Dice score of 0.93 ± 0.06 for other bones (skull, mandible, scapulae, clavicles, humeri and hyoid), 0.93 ± 0.02 for ribs and 0.88 ± 0.03 for vertebrae on 7 test cases from the same cohorts as the training datasets. We compared our proposed solution approach to a retrained nnU-Net and obtained comparable results for vertebral bones while outperforming in the correct identification of the left and right instances of ribs, scapulae, humeri and clavicles. Furthermore, we evaluated the generalization capability of our proposed model on a new cohort and the mean Dice score yielded 0.96 ± 0.10 for other bones, 0.95 ± 0.07 for ribs and 0.81 ± 0.19 for vertebrae on 8 test cases.Significance.With these insights, we are challenging the utilization of an automatic and accurate bone segmentation tool into the clinical routine of radiotherapy despite the limited training datasets.

Design and evaluation options of multimedia applications to support the care of people with mild dementia

In order to cognitively and physically activate people with dementia (MMD) in institutional settings, there are numerous touch-based multimedia applications specifically designed for this target group that are actually being used in practice. In contrast, the use of similar applications in domestic settings has been relatively limited. This study is based on 11expert interviews guided by questions and examines design options and requirements for application content as well as requirements for study designs to provide evidence of the effectiveness of touch-based multimedia applications for MMD and their caregiving relatives (PA). There is ahigh degree of consensus regarding the criteria for requirements for touch-based multimedia applications. Acceptance is highly dependent on user competence, usage practices, experiences and incentive structures; however, there are diverse opinions about their structural and content-related design. The quality of life is mentioned as an essential evaluation parameter for multimedia applications. The highly variable individual life circumstances of MMD and their PAs, along with limited access options and alack of suitability of the multimedia applications, may be causal factors for their relatively limited use, especially in domestic settings. Daily performance capabilities and individual disease progression pose special requirements for the scientific evaluation and the demonstration of the effectiveness of touch-based multimedia applications.

A single-stage dual-source inverter using low-power components and microcomputers

This paper is an attempt to provide a dual-source inverter, an intelligent inverter topology that links two isolated DC sources to a single three-phase output through single-stage conversion. The converter is designed to be utilized in hybrid photovoltaic fuel cell systems, among other renewable energy applications. The proposed dual-source inverter employs a single DC-AC converter, as opposed to conventional dual-source hybrid inverters which make use of several input DC-DC modules to obtain the voltage formed across the inverter’s input DC-link. In the proposed topology, the semiconductor count is low, which leads to improved efficiency, cost, complexity, and reliability. The proposed topology makes use of two impedance networks connected by transformers, diodes, and capacitors. The regulation of the electrical power generated by primary sources and the independence of the converter on key factors like voltage and frequency are essential parameters in multi-input converters. This feature becomes highly prominent when the control algorithm is implemented by conventional processors. Viewed from this perspective, the control method described in this paper is worthy of consideration. The research work describes a 220-W/50 Hz prototype that employs Simple Boost-SPWM. Experimental results verify the analyses and corroborate the satisfactory performance of the suggested converter.

An AI-based framework for earthquake relief demand forecasting: A case study in Türkiye

Accurately forecasting the demand for relief assistance is crucial for efficient post-disaster relief operations. This paper presents an AI-based framework for earthquake relief demand forecasting, aiming to optimize the distribution of emergency resources. To identify higher-risk areas, the framework integrates historical earthquake data with socioeconomic information. This information aids in identifying regions that require immediate relief assistance. The initial dataset for relief demand quantification includes essential parameters such as Latitude, Longitude, Population, Demand, Supply, Cost, Deaths, Injuries, Infrastructural Damage, and Cascading Disaster. By analyzing these inputs and factors, AI algorithms can quantify the relief demand scenario accurately, resulting in accurate and reliable forecasts of relief supply requirements. The iterative ML techniques in generating comprehensive data for Türkiye greatly enhance the quality and accuracy of relief demand prediction. The prediction models used in the framework, namely Least Angle Regression and Linear Regression, demonstrate exceptional performance in forecasting relief demand. They achieve a remarkable R2 score of 1, indicating a perfect fit to the data, and a Loss Error function value of zero, signifying highly accurate predictions. Additionally, the Decision Tree algorithm showcases strong capabilities in iterative learning, achieving an accuracy rate of 88.99 %. In addition to providing valuable insights for tailored relief strategies, the framework extends beyond relief demand by predicting outcomes such as casualties, injuries, and infrastructure damage. With a comprehensive understanding of the earthquake’s impact, relief organizations can strategize their response and allocate resources accordingly. The thorough methodology and innovative application of ML algorithms within our pioneering AI-based framework significantly contribute to the field. This signifies a fundamental shift in the approach to envisioning and executing relief operations following seismic events.

Dynamic plastic hinge rotation measurement for RC columns under seismic loads using MEMS inclinometers

Plastic hinge rotation is an efficient and essential response parameter for post-disaster damage assessment on RC structures. In this paper, a micro-electronic mechanical system (MEMS) inclinometer-based approach is developed to dynamically measure the plastic hinge rotation of RC columns under earthquake loads. The plastic hinge rotation is regarded as the relative angle of rotation, measured by inclinometers, between cross-sections such that influence from the absolute rotation of floors can be eliminated. Meanwhile, since the inclinometers are densely installed near the bottom, translational acceleration-induced error can be compensated by subtracting the lowest sensor’s output from others’. However, issues caused by rotational and translational vibration are considered as the major challenges in real applications. The contribution of external vibration to the sensor’s overall output is revealed via analysis on a simplified inclinometer model. A numerical study utilizing typical RC column’s deformation characteristics and dimensions is conducted to analyze the influence of major factors: vibrational frequency, sensor position and damage extent. A method for static and dynamic inclinometer calibration is presented. The related calibration experiments are carried out to quantify the sensor’s sensitivity as well as the relationship between rotational frequency and error. The calibration method is validated with a set of vibration tests that use three seismic waves as input. Finally, performance of the proposed approach in full scale structures is investigated through a shake table test.

HPLC-MS/MS Analysis for Sphingosine 1-Phosphate after the Dephosphorylation by Hydrogen Fluoride

Sphingosine 1-phosphate (S1P) is a signaling lipid molecule involved in various cellular processes. It is important to develop a quantitative method for S1P to determine endogenous levels and to investigate its functions. As S1P is a tiny lipid component of most biological samples, highly sensitive analysis by LC-MS/MS is required. The main challenge in S1P analysis by chromatography is peak-broadening due to the presence of a polar phosphate and the fact that S1P is indeed a zwitterion itself. In this study, we used hydrogen fluoride (HF) to efficiently remove a phosphate and then analyzed the surrogate, sphingosine, as a sharp peak by LC-ESI-MS/MS. We optimized the dephosphorylation reaction in terms of temperature and reaction time. Multiple reaction monitoring (MRM) for a dephosphorylated form of S1P and C17-S1P as an internal standard at m/z transition 300.4 &gt; 282.4 (quantification ion), 300.4 &gt; 262.4 (qualification ion), 286.3 &gt; 268.2 (internal standard) was conducted. This method was validated by essential parameters such as specificity, linearity, range, LOQ, LOD, accuracy, precision, and repeatability. To confirm this new method, we quantified S1P levels in various serum products (100.0~284.4 nM). In the sample pretreatment conditions for extracting S1P, the concern about potential sphingosine contamination in serum was negligible. The dephosphorylation efficiency by this method was about two-fold higher than that of alkaline phosphatase (APase). To apply the method in vivo, we analyzed S1P in plasma and kidney tissues obtained from a chronic kidney disease (CKD) mouse model. S1P levels were increased only in CKD kidney tissue but not in plasma. In conclusion, by applying the dephosphorylation step with HF, we established a new, sensitive LC-MS/MS quantitative method for S1P that can be applied to biological samples.

Waste Sludge: Entirely Waste or a Sustainable Source of Biocrude? A Review.

Biomass-derived biocrude is gaining greater recognition from people in general as an alternative fuel source to traditional fossil fuels. Worldwide, a great deal of research is being done to develop fuels made from sustainable biomass in order to replace the current conventional energy sources. Waste sludge has been thought of as a viable raw biomass source because of its accessibility, affordability, high lignin content, and higher heating value. Additionally, considering sludge contains a high proportion of moisture and water acts as a catalyst during the hydrothermal liquefaction (HTL) process, it is the best choice for thermochemical conversion. From the ultimate component value ranges obtained from elemental analysis, it can be demonstrated that the C, H, and higher heating value (HHV) of petrocrude are approximately 8.78%, 23.5%, and 10.66% higher than those of biofuel. According to the overall analysis, co-liquefaction of waste vegetable oil and swine manure can result in 87.97% bio-oil at 340°C. The temperature, retention period, inclusion of catalysts, and use of solvents, however, can all affect this proportion. To support this illustration, it has been assessed from the study that municipal wet sewage sludge can produce an HHV of 28.52MJ/kg when water is used as the solvent. However, 34.14MJ/kg, or 16.5% more than the previous one, can be produced for the same amount of biomass, when the mixture of water and methanol serves as the solvents. This review article highlights an array of waste sludge categories, their chemical properties, and their conversion through the HTL process. It also features a Van Krevlen diagram with a graphical representation of essential operating parameters. This review research illustrates one of the best strategies for producing biofuel in which waste sludge can be used as raw material through the HTL conversion process, considering the prospective mass commercial production of biocrude oil.