High Ability Research Articles

Which one is more accurate, BILOG or R program? (a comparison for score test equating)

Evaluation may be carried out using different tests that are not necessarily parallel. Students with lower abilities may get higher scores while those with higher abilities get lower scores. Measurement errors caused by this condition require test equating. Several computer programs, including Bilog and the R program, can be used for test equating. Each program has a different level of accuracy, and the accuracy of the equating results will affect the standard errors of equating. This study aimed to find out the most accurate equating test method and the accuracy of the estimated BILOG and R program. This research used two sets of tests with equivalent group designs. The determination of the most accurate equating method was based on the root mean square deviation (RMSD) value. Equating test packages, A to package B with BILOG program estimation on the mean and Sigma method resulted in RMSD value of 0.320. In the mean and mean method, RMSD value is 0.250. Meanwhile, equating package A to package B using R program on the mean and sigma resulted in RMSD value of 0.300, and the mean and mean method with the RMSD value is 0.272. The mean and mean yield RMSD values smaller than the mean and sigma methods. Therefore, the mean and mean method is more accurate and applicable. Moreover, the estimation results of the BILOG program are more accurate and can be used in test equating.

High nitrogen removal and electricity generation of anaerobic fluidized bed coupled microbial fuel cell for Anammox

The current challenge in wastewater denitrification lies in the treatment of low carbon to nitrogen ratio(C/N) wastewater. Integrating Anaerobic Ammonia Oxidation(Anammox) with a microbial fuel cell(MFC) enables simultaneous pollutant removal and electricity generation, leading to enhanced treatment efficiency and reduced energy consumption. However, achieving stable and effective treatment effects under high nitrogen concentration conditions remains a general research difficulty. The Anaerobic fluidized bed MFC(AFB-MFC) experiment successfully integrated Anammox ammonia oxidizing bacteria (AnAOB) into the anode and cathode chambers, resulting in a continuous operation for 258 days. The reactor successfully initiated operation within 48 days and maintained stable performance within an NLR range of 0.5-1.0 kgN/m3/d. The system performance was found to be influenced by DO and substrate concentration, demonstrating consistent high nitrogen removal ability across different HRT. Ultimately, the Anammox AFB-MFC achieved a nitrogen removal efficiency (NRE) of 96.89%, while its power generation performance gradually improved, yielding a final output voltage ranging from 370 to 420mV. The microbial community within the reactor comprised diverse electricity-producing bacteria and AnAOB. This study highlights the excellent denitrification and power generation potential of Anammox AFB-MFC under low energy consumption conditions and provides theoretical groundwork for the practical implementation of Anammox.

Combined Gas Tungsten Arc Welding and Shielded Metal Arc Welding Processes for Joining Tube to Tubesheet in Shell and Tube Heat Exchangers

Abstract Flawless tube and tubesheet joints are necessary for shell and tube heat exchanger with high leakproof ability and durability. The consequence of mixing of transfer fluids due to the defective welded or expanded tube-to-tubesheet joint results in complete malfunctioning of the heat exchange process. In this case, there is a high demand for quality assessment of the fabricated tube-to-tubesheet joints (TTS) based on the international standards. Additionally, the literature on assessing the mechanical and metallurgical characteristics of tube-to-tubesheet joints using any one welding technique is available; however, articles dealing with the use of multiple welding techniques are scanty. In the current work, the quality assessment of strength welded and light expanded (3%) tube-to-tubesheet joints followed by light expansion was performed whereas for welding, combined gas tungsten arc welding (GTAW) and shielded metal arc welding (SMAW) as root pass and cap pass were adopted in the fabrication stage. Quality and sound tube-to-tubesheet joints were produced using welding and tube expansion process. Linear and circular indications representing the cracks were absent on the developer in the liquid penetration test. The minimum leak path (MLP) was greater than the two-third of tube wall thickness. The results strongly qualify the use of combined gas tungsten inert gas and shielded metal arc welding process for manufacturing of tube-to-tubesheet joints. The methodology and results in the current article are beneficial for researchers and industrialists working close to shell and tube heat exchangers and boilers.

Evaluating Performance of Multiple Machine Learning Models for Drought Monitoring: A Case Study of Typical Grassland in Inner Mongolia

Driven by continuously evolving precipitation shifts and temperature increases, the frequency and intensity of droughts have increased. There is an obvious need to accurately monitor drought. With the popularity of machine learning, many studies have attempted to use machine learning combined with multiple indicators to construct comprehensive drought monitoring models. This study tests four machine learning model frameworks, including random forest (RF), convolutional neural network (CNN), support vector regression (SVR), and BP neural network (BP), which were used to construct four comprehensive drought monitoring models. The accuracy and drought monitoring ability of the four models when simulating a well-documented Inner Mongolian grassland site were compared. The results show that the random forest model is the best among the four models. The R2 range of the test set is 0.44–0.79, the RMSE range is 0.44–0.72, and the fitting accuracy relationship could be described as RF > CNN > SVR ≈ BP. Correlation analysis between the fitting results of the four models and SPEI found that the correlation coefficient of RF from June to September was higher than that of the other three models, though we noted the correlation coefficient of CNN in May was slightly higher than that of RF (CNN = 0.79; RF = 0.78). Our results demonstrate that comprehensive drought monitoring indices developed from RF models are accurate, have high drought monitoring ability, and can achieve the same monitoring effect as SPEI. This study can provide new technical support for comprehensive regional drought monitoring.

Discovery of seed germinating fungi (Mycetinis scorodonius) from Gastrodia elata Bl. f. glauca S. chow in Changbai Mountain and examination of their germination ability

Multi-generational asexual reproduction of Gastrodia elata Bl. will cause seedling species degeneration. Sexual reproduction of Gastrodia elata Bl. seed is an effective method to solve the problem of degeneration. The development of Gastrodia elata Bl. seeds cannot be separated from the germination fungus. However, there are few strains of germination fungus in production, and there is also the problem of species degradation in application for many years. It is very important for the sexual reproduction of Gastrodia elata Bl. to isolate more new strains of excellent germination fungus from the origin. This study used the Gastrodia elata Bl. f. glauca S. chow seeds germination vegetative propagation corms capture method to isolate its symbiotic germination fungus, and comprehensively identified the species of germination fungus by colony morphology, ITS, sporocarps regeneration and germination function, and compared the growth characteristics and germination ability with other germination fungus (Mycena purpureofusca, Mycena dendrobii and Mycena osmundicola). The germination fungus was isolated from the vegetative propagation corms of Gastrodia elata Bl. f. glauca S. chow seeds and named GYGL-1. After comprehensive identification, GYGL-1 was Mycetinis scorodonius. Compared with other germination fungus, GYGL-1 has fast germination speed, vigorous growth, and high germination ability for Gastrodia elata Bl. f. glauca S. chow seeds. Innovated the isolation method of Gastrodia elata Bl. seeds germination fungus, obtained the regenerated sporocarps of the germination fungus, and discovered that Mycetinis scorodonius has a new function of germinating Gastrodia elata Bl. f. glauca S. chow seeds, enriching the resource library of Gastrodia elata Bl. germination fungus.

An integrated smartphone-based electrochemical detection system for highly sensitive and on-site detection of chemical oxygen demand by copper-cobalt bimetallic oxide-modified electrode.

Aportable and integrated electrochemical detection system has been constructed for on-site and real-time detection of chemical oxygen demand (COD). The system mainly consists of four parts: (i) sensing electrode with a copper-cobalt bimetallic oxide (CuCoOx)-modified screen-printed electrode; (ii) an integrated electrochemical detector for the conversion, amplification, and transmission of weak signals; (iii) a smartphone installed with a self-developed Android application (APP) for issuing commands, receiving, and displaying detection results; and (iv) a 3D-printed microfluidic cell for the continuous input of water samples. Benefiting from the superior catalytic capability of CuCoOx, the developed system shows a high detection sensitivity with 0.335 μA/(mg/L) and a low detection limit of 5.957 mg/L for COD determination and possessing high anti-interference ability to chloride ions. Moreover, this system presents good consistency with the traditional dichromate method in COD detection of actual water samples. Due to the advantages of cost effectiveness, portability, and point-of-care testing, the system shows great potential for water quality monitoring, especially inresource-limited remote areas.

Novel controllable (Ba0.8Sr0.2)CO3@Mesoporous silicate core/shell nanocomposite grafted fluorescent probes for colorimetric, sensing, and selective detection of heavy metals

Fluorescent nanosensors are one of the most efficient techniques used for detection of toxic metal ions, based on ligand embedded into mesoporous materials. In this study, four different novel nanosensors NS1, NS2, NS3, and NS4 have been synthesized by incorporating fluorescent probes containing dihydropyridine and dihydropyrimidinone fragments into amino‐functionalized controllable (Ba0.8Sr0.2)CO3@Mesoporous silicate core/shell nanocomposite. The designed nanosensors were characterized by FT‐IR (Fourier‐transform infrared spectroscopy), X‐ray diffraction, transmission electron microscopy (TEM), and nitrogen adsorption–desorption isotherms. Visual naked‐eye observations and emission technique were employed to investigate the recognition and sensing capability of the investigated nanosensors toward various metal ions (Al3+, Cr3+, Mn2+, Fe3+, Co2+, Ni2+, and Cu2+). A great quenching in the fluorescence intensity was clearly observed with the majority of studied metal ions for all the nanosensors. The binding constants and limit of detection (LOD) have been calculated. Cu2+ is the strongest binded one with both NS1 and NS2, while Al3+ and Fe3+ are the strongest binded metal ions with NS3 and NS4, respectively. The obtained results confirmed the high ability of the nanosensors to detect heavy metals ions at environmentally relevant concentrations using simple and low‐cost experimental studies with good reversibility and reusability.

Detoxification of Chemical Warfare Agents by a Zr‐Based MOF with High Recycling Ability at Physiological pH

The neutralization of organophosphorous (OP) chemical agents used in modern warfare is a growing concern due to their extreme toxicity to human cells. In several previous works, although the capability of several Zr‐MOF‐based catalysts has been showcased to facilitate hydrolysis of OP agents in heterogeneous pathways, their usage appeared to be limited by very slow kinetics at neutral pH. There is still a lack of MOF based catalysts that can detoxify OPs at physiological pH. The recycling ability of MOF‐based catalysts has also not been greatly explored. Thus, herein, we explored a Zr‐based MOF, MOF‐801(Zr) for the detoxification of a series of OP nerve agents and a pesticide with simultaneous adsorption and degradation at pH 7.5 in a buffer solution, close to physiological conditions. This MOF‐based catalyst demonstrates significant hydrolysis activity towards several nerve agents, with up to 99% conversion within 2 h and an excellent half‐life of less than 5 minutes. In addition, it can be recycled at least 5 times consecutively with a residual activity of at least 90%.

First-principles screening of XSbF3 (X = Ba and Ra) fluoroperovskites: an insight into structural, optoelectronic and thermal properties

This work presents a computational study of the physical properties such as structural, electronic, optical and thermal properties of XSbF3 (X = Ba and Ra) fluoroperovskites. The calculations were performed using the density functional theory (DFT) calculations in conjunction with Quantum Espresso code. The stability of the crystal structure XSbF3 compounds is determined by binding energy (Eb) computations. The Eb values for BaSbF3 and RaSbF3 compounds are −19.25 and −20.04eV respectively, indicating that both studied compounds are stable. The optimized lattice constants for BaSbF3 and RaSbF3 compounds are 5.03 and 5.06 Å, respectively. The evaluation of electronic properties is conducted by electronic band structure, total density of states (DOS), and partial density of states (PDOS). It is observed from the PDOS plots that the p-states of Sb and F whereas the d-states of X atoms have the major contribution in the formation of the band structure. Various optical properties have been computed and compared. The static value of ε10 highlights the metallic nature of the studied compounds while RaSbF3 stands out for having the highest recorded value of ε20. The maximum nω values for BaSbF3 and RaSbF3 are 8.46 and 6.86 respectively indicating their potential for photoelectric applications. Furthermore when examining the properties it is evident that the BaSbF3 compound stands out as a material for energy storage because of its higher electron energy at 2.36 KJ/N.mol and lower electron free energy of −2.55 KJ/N.mol compared to the RaSbF3 compound. On the other hand, the RaSbF3 compound is an efficient material for catalysis due to its high ability to absorb heat energy from the external source, as compared to the BaSbF3 compound. This study is the first computational investigation of XSbF3 (X is Ba and Ra) compounds, which provides valuable insights into the physical properties of sb-based fluroperovskites and their potential applications.

GHz-rate 57-fs acousto-optic mode-locking fiber laser based on cascaded all-fiber pulse compression

We demonstrate a compact ultrafast fiber laser system that can deliver 1.87 GHz pulse train at 1550 nm with a pulse energy of 52 pJ and an ultrashort pulse duration of 57 fs. While an acousto-optic mode-locking fiber laser was used as the seed light source at GHz rate, a stage of Er-doped fiber amplifier boosted the laser power to ∼320 mW, giving a pulse energy of ∼170 pJ. Then, a pulse compression setup was constructed, providing a high compression ratio of ∼10 with a total efficiency of ∼32%. In the cascaded compression configuration, multiple fiber samples with alternately normal and anomalous dispersion were fused together, providing efficient nonlinear spectral broadening while suppressing excessive pulse broadening over propagation. This GHz-rate ultrafast fiber laser, with compact configuration, broad optical spectrum, and high time-resolving ability could be used as the seed light source for constructing high-rate, high-power ultrafast laser systems and may find a few applications in optical measurements and microwave photonics.

Speckle visual cryptography for credential authentication

Based on the high random distribution characteristic of the natural speckle image, a new method of speckle visual cryptography, to the best of our knowledge, is designed by combining the natural speckle image with the secret key in visual cryptography. Specifically, we designed an authentication system for user credentials by combining speckle visual cryptography and the QR code. By using the speckle visual cryptography method, the image of the QR code carrying user authentication information is hidden in the speckle image, and the speckle image is printed on the paper credentials. Through a simulation and analog experiments, we verify the possibility of applying speckle visual cryptography to a user credentials authentication system, compare the improved grayscale reordering algorithm and grayscale reordering algorithm, and prove that the improved grayscale reordering algorithm has more advantages in this system by comparing the PSNR and SSIM. Finally, the y-interference ability and the uniqueness of the virtual secret key in the system are analyzed to prove that the secret key has high anti-interference ability and security.

Polysaccharide‐Modified SnO2 for Highly Efficient Perovskite Solar Cells

Tin oxide (SnO2) has been demonstrated as a promising electron transport material for perovskite solar cells (PSCs) due to its low‐temperature process and high charge extraction ability. However, the key to improving the internal performance of PSCs toward unity lies in the ability of enhancing bulk SnO2 quality and reducing the energy level mismatch between SnO2 and perovskite layer. Herein, a facile and effective strategy to simultaneously functionalize SnO2 structure by sodium alginate (SA) polysaccharide compound is reported. The investigations reveal that SA leads to the formation of nanosynapse structure of SnO2 films, which allows the aligned energy levels and suppressed charge recombination, significantly enhancing carrier extraction and transport. Consequently, CsMAFAPb(IxBr1−x)3 and CsPbI2Br solar cells achieve a remarkable power conversion efficiency of 24.11% and 16.90%, respectively, based on SnO2‐SA electron transport layers (ETLs). This work offers a facile and effective way to fabricate high‐performance SnO2 ETL in PSCs.

Synthesizing hard carbon anodes for potassium-ion batteries from black liquor and deinking sludge

Porous hard carbon anodes, with large interlayer space and high adsorption ability, can offer much better cycle stability and higher discharge capacity for potassium-ion batteries compared to commercial graphite anodes. However, most commercial hard carbons are synthesized from relatively expensive high-molecular polymers. In this study, pulping and papermaking wastes were utilized as precursors for producing hard carbons and pore-enlarging agent, respectively. Specifically, after thorough mixing through ball milling, black liquor solids and deinking sludge were utilized to produce porous hard carbon anodes via co-pyrolysis. The results show that direct pyrolysis of black liquor can produce hard carbons efficiently, eliminating the need to extract lignin from black liquor. Moreover, it is shown that the pore-enlarging agent derived from deinking sludge can enlarge much portion of pores on hard carbons, resulting in abundant mesopores. Electrochemical tests demonstrate that the synthesized porous hard carbon anodes can achieve highest specific capacity of 303.5 mAh g−1 at 100 mA g−1 using a 1.0 M potassium hexafluorophosphate electrolyte in a mixture of diethyl carbonate and ethylene carbonate. Additionally, the synthesized porous hard carbon anodes exhibit low average capacity decay per cycle of 0.06 % at 100 mA g−1 when tested with a 1.0 M potassium bis(fluorosulfonyl)imide electrolyte in the same solvent mixture after 500 cycles. Therefore, recycling black liquor and deinking sludge to produce porous hard carbon anodes for potassium-ion batteries is a promising approach for environmental and energy sustainability.

Comparison of the Differences between Two-Photon Excitation, Upconversion, and Conventional Photodynamic Therapy on Cancers in In Vitro and In Vivo Studies

Photodynamic therapy (PDT) is a minimally invasive treatment for several diseases. It combines light energy with a photosensitizer (PS) to destroy the targeted cells or tissues. A PS itself is a non-toxic substance, but it becomes toxic to the target cells through the activation of light at a specific wavelength. There are some limitations of PDT, although it has been used in clinical studies for a long time. Two-photon excitation (TPE) and upconversion (UC) for PDT have been recently developed. A TPE nanoparticle-based PS combines the advantages of TPE and nanotechnology that has emerged as an attractive therapeutic agent for near-infrared red (NIR) light-excited PDT, whilst UC is also used for the NIR light-triggered drug release, activation of ‘caged’ imaging, or therapeutic molecules during PDT process for the diagnosis, imaging, and treatment of cancers. Methods: Nine electronic databases were searched, including WanFang Data, PubMed, Science Direct, Scopus, Web of Science, Springer Link, SciFinder, and China National Knowledge Infrastructure (CNKI), without any language constraints. TPE and UCNP were evaluated to determine if they had different effects from PDT on cancers. All eligible studies were analyzed and summarized in this review. Results: TPE-PDT and UCNP-PDT have a high cell or tissue penetration ability through the excitation of NIR light to activate PS molecules. This is much better than the conventional PDT induced by visible or ultraviolet (UV) light. These studies showed a greater PDT efficacy, which was determined by enhanced generation of reactive oxygen species (ROS) and reduced cell viability, as well as inhibited abnormal cell growth for the treatment of cancers. Conclusions: Conventional PDT involves Type I and Type II reactions for the generation of ROS in the treatment of cancer cells, but there are some limitations. Recently, TPE-PDT and UCNP-PDT have been developed to overcome these problems with the help of nanotechnology in in vitro and in vivo studies.

Mindfully missing myself: Induced mindfulness causes alienation among poor self-regulators.

Mindfulness is a popular technique that helps people to get closer to their self. However, recent findings indicate that mindfulness may not benefit everybody. In the present research, we hypothesized that mindfulness promotes alienation from the self among individuals with low abilities to self-regulate affect (state-oriented individuals) but not among individuals with high abilities to self-regulate affect (action-oriented individuals). In two studies with participants who were mostly naïve to mindfulness practices (70% indicated no experience; N1 = 126, 42 men, 84 women, 0 diverse, aged 17-86 years, Mage = 31.87; N2 = 108, 30 men, 75 women, 3 diverse, aged 17-69 years, Mage = 28.00), we tested a mindfulness group (five-minute mindfulness exercise) against a control group (five-minute text reading). We operationalized alienation as lower consistency in repeated preference judgments and a lower tendency to adopt intrinsic over extrinsic goal recommendations. Results showed that, among state-oriented participants, mindfulness led to significantly lower consistency of preference judgments (Study 1) and lower adoption of intrinsic over extrinsic goals (Study 2) compared to text reading. The alienating effect was absent among action-oriented participants. Thus, mindfulness practice may alienate psychologically vulnerable people from their self and hamper access to preferences and intrinsic goals. We discuss our findings within Personality-Systems-Interactions (PSI) theory.

Strong Covalent Coupling in Vertically Layered SnSe2/PTAA Heterojunctions Enabled High Performance Inorganic-Organic Hybrid Photodetectors.

Controllable large-scale integration of two-dimensional (2D) materials with organic semiconductors and the realization of strong coupling between them still remain challenging. Herein, we demonstrate a wafer-scale, vertically layered SnSe2/PTAA heterojunction array with high light-trapping ability via a low-temperature molecular beam epitaxy method and a facile spin-coating process. Conductive probe atomic force microscopy (CP-AFM) measurements reveal strong rectification and photoresponse behavior in the individual SnSe2 nanosheet/PTAA heterojunction. Theoretical analysis demonstrates that vertically layered SnSe2/PTAA heterojunctions exhibit stronger C-Se covalent coupling than that of the conventional tiled type, which could facilitate more efficient charge transfer. Benefiting from these advantages, the SnSe2/PTAA heterojunction photodetectors with an optimized PTAA concentration show high performance, including a responsivity of 41.02 A/W, an external quantum efficiency of 1.31 × 104%, and high uniformity. The proposed approach for constructing large-scale 2D inorganic-organic heterostructures represents an effective route to fabricate high-performance broadband photodetectors for integrated optoelectronic systems.

Layers of Mathematical Understanding and Folding Back of Prospective Teachers on Arithmetic Sequence and Series

Mathematical understanding is one of the objectives of learning mathematics, so students need to master it. The success of the process of growing students' mathematical understanding is inseparable from the role of the teacher. Therefore, student teacher candidates must have a complete mathematical understanding structure. This is what prompted him to carry out research to describe the layers of mathematical understanding and folding back prospective teacher students on the material of arithmetic sequences and series. The researcher took 18 sixth-semester students of S1 Mathematics Education at the State University of Malang. A purposive sampling technique was used to determine the participants. So, one subject was chosen in each category of mathematical understanding. Researchers used a descriptive approach with three stages of research procedures including planning, implementing, and drawing conclusions. The instruments used consisted of test questions and interview guidelines. Based on analysis carried out using indicators for each layer of mathematical understanding, information was obtained that subjects with high abilities were able to achieve layering arrangement and perform effective folding back independently. Subjects with moderate abilities were able to reach the observation layer and fold back effectively but needed help. Meanwhile, subjects with low abilities were able to reach the formalization layer but had not been able to fold back effectively. It can be concluded that subjects with better mathematical understanding have a more complete layered structure of mathematical understanding and can fold back independently and effectively.

Construction of a nomogram based on clinicopathologic features to predict the likelihood of No. 253 lymph node metastasis in rectal cancer patients.

To explore the high-risk factors for rectal cancer No.253 lymph node metastasis (LNM) and to construct a risk nomogram for the individualized prediction of No.253 LNM. This was a retrospective analysis of 425 patients with rectal cancer who underwent laparoscopic-assisted radical surgery. Independent risk factors for rectal cancer No.253 LNM was identified using multivariate logistic regression analysis, and a risk prediction nomogram was constructed based on the independent risk factors. In addition, the performance of the model was evaluated by discrimination, calibration, and clinical benefit. Multivariate logistic regression analysis showed that No.253 lymphadenectasis on CT (OR 10.697, P < 0.001), preoperative T4-stage (OR 4.431, P = 0.001), undifferentiation (OR 3.753, P = 0.004), and preoperative Ca199 level > 27 U/ml (OR 2.628, P = 0.037) were independent risk factors for No.253 LNM. A nomogram was constructed based on the above four factors. The calibration curve of the nomogram was closer to the ideal diagonal, indicating that the nomogram had a better fitting ability. The area under the ROC curve (AUC) was 0.865, which indicated that the nomogram had high discriminative ability. In addition, decision curve analysis (DCA) showed that the model could show better clinical benefit when the threshold probability was between 1% and 50%. Preoperative No.253 lymphadenectasis on CT, preoperative T4-stage, undifferentiation, and elevated preoperative Ca199 level were found to be independent risk factors for the No.253 LNM. A predictive model based on these risk factors can help surgeons make rational clinical decisions.

Aerosol Doping System for Microscale Seamless p-n Patterning of Carbon Nanotube Films.

Carbon nanotube (CNT) films are extensively researched as a promising material for wearable thermoelectric generators (TEGs) owing to their good flexibility and high thermoelectric conversion ability. Miniaturizing a pair of p- and n-type thermocouples and increasing the number of repeating elements can effectively increase the power of TEGs. However, conventional p-n patterning methods, such as dipping and printing, have a coarse resolution at the submillimeter level, thereby limiting the miniaturization rate. This study developed an aerosol doping system as a fine n-doping method. A dopant aerosol with a <3 μm diameter was formed through ultrasonic nebulization and air separation, while n-doping was achieved by exposing the CNT film to the dopant aerosol. Microscale p-n patterning of 1 μm was achieved through exposure using small-sized aerosols at an exceptionally slow rate of 3 Å/min. This resolution is 100 times higher than those of conventional p-n patterning methods. The developed aerosol doping system for CNTs can also be used on organic semiconductor materials, such as PEDOT/PSS and perovskite materials. Therefore, it has the potential to significantly impact the realization of Internet of Things (IoT) terminals, such as flexible TEGs, transistors, and solar cells.

A reduced proteomic signature in critically ill Covid-19 patients determined with plasma antibody micro-array and machine learning

BackgroundCOVID-19 is a complex, multi-system disease with varying severity and symptoms. Identifying changes in critically ill COVID-19 patients’ proteomes enables a better understanding of markers associated with susceptibility, symptoms, and treatment. We performed plasma antibody microarray and machine learning analyses to identify novel proteins of COVID-19.MethodsA case-control study comparing the concentration of 2000 plasma proteins in age- and sex-matched COVID-19 inpatients, non-COVID-19 sepsis controls, and healthy control subjects. Machine learning was used to identify a unique proteome signature in COVID-19 patients. Protein expression was correlated with clinically relevant variables and analyzed for temporal changes over hospitalization days 1, 3, 7, and 10. Expert-curated protein expression information was analyzed with Natural language processing (NLP) to determine organ- and cell-specific expression.ResultsMachine learning identified a 28-protein model that accurately differentiated COVID-19 patients from ICU non-COVID-19 patients (accuracy = 0.89, AUC = 1.00, F1 = 0.89) and healthy controls (accuracy = 0.89, AUC = 1.00, F1 = 0.88). An optimal nine-protein model (PF4V1, NUCB1, CrkL, SerpinD1, Fen1, GATA-4, ProSAAS, PARK7, and NET1) maintained high classification ability. Specific proteins correlated with hemoglobin, coagulation factors, hypertension, and high-flow nasal cannula intervention (P < 0.01). Time-course analysis of the 28 leading proteins demonstrated no significant temporal changes within the COVID-19 cohort. NLP analysis identified multi-system expression of the key proteins, with the digestive and nervous systems being the leading systems.ConclusionsThe plasma proteome of critically ill COVID-19 patients was distinguishable from that of non-COVID-19 sepsis controls and healthy control subjects. The leading 28 proteins and their subset of 9 proteins yielded accurate classification models and are expressed in multiple organ systems. The identified COVID-19 proteomic signature helps elucidate COVID-19 pathophysiology and may guide future COVID-19 treatment development.