Processing Methods Research Articles

Functionalized nitrogen-enrich graphene as a highly efficient photocatalyst for oxidative cyclization of thioamide and degradation of Dye

Functionalized photocatalysts have shown to be an effective method for oxidative cyclization processes and the degradation of organic poisons like chemicals and dyes. In this study, we report the facile, environmentally friendly, room-temperature (RT) synthesis and development of a graphene-based visible light active photocatalyst (NenG-RhB) which is thermodynamically converted to nitrogen-enriched graphene (NenG) covalently bonded to a light-harvesting RhB molecule [9-(2-Carboxyphenyl)-6-(diethylamino)-N, N‑diethyl-3H-xanthen-3-iminium chloride)]. The NenG-RhB photocatalyst is extremely effective, resulting in good oxidative cyclization of aromatic thioamide (92.5 %) and degradation efficiency of industrial orange G (97.29 %) under solar light. The current research focuses on the invention and implementation of a nitrogen-enrich graphene-based photocatalyst for direct solar medicinal chemical synthesis and industrial dye degradation in wastewater using solar light.

Nutritional Characteristics and Sensory Properties of Maize-based Ogi Supplemented with Mushroom (Pleurotus ostreatus) Flour

The study evaluates the effect of supplementation of maize-based ogi with mushroom (Pleurotus ostreatus) flour on nutritional characteristics and sensory properties. Standard processing and analytical methods were used in raw material preparation and analyses. Ogi and mushroom flour were blended in ratio of 100:0, 90:10, 80:20, 70:30 and labeled A, B, C and D respectively. A commercial maize based complementary food was used as control. There was significant difference (p < 0.05) among all samples for all the Vitamin assayed with values ranging from 4.86 to 9.06 (µg/100g), 0.32 to 1.09 mg/100 g, 0.22 to 0.69 mg/100 g, 3.82 to 13.03 mg/100 g and 0.13 to 1.12 mg/100 g for vitamin A, B1, B2, B3 and C. The vitamin values compare favourably with that of control sample. Significant (P<0.05) difference exists across the samples for Zn, Mg, Fe, K and Ca with values ranging from 1.12 to 1.71 mg/100 g, 37.7 to 102 mg/100 g, 4.72 to 13.23 mg/100 g, 23.05 to 125.3 mg/100 g and 125.5 to 160.25 mg/100 g respectively with corresponding higher values for control sample. Result showed negligible amounts of anti-nutritional factors ranging from 0.29 to 0.36 mg/100 g, 0.02 to 0.03 mg/100 g, 0.03 to 0.06 mg/100 g and 0.56 to 0.83 mg/100 g for phytate, oxalate, trypsin inhibitor and tannin respectively. The functional properties of the flour blends values ranged from 0.58 to 0.72 g/mL, 0.99 to 2.2 g/g, 5.21 to 8.94 g/g, 1.75 to 3.72 mL/g and 5.5 to 9.0% for bulk density, water absorption capacity, water retention capacity, swelling capacity and least gelation concentration respectively. Sensory scores revealed substantial overall acceptability of the samples. The quality of ogi samples were greatly improved by mushroom supplementation and could be nutritional beneficial to children and adults.

Antioxidant Activity, Theaflavin, Total Polyphenol, and Catechin Composition of Camellia sinensis Processing Effluents from Various Factories in Kenya

Research into the antioxidant efficacy and sustainability implications of tea waste, a by-product of the rapidly growing global beverage industry, is increasingly necessary. This study scrutinized samples taken from various factories to explore their capacity for free radical scavenging and potential public health and environmental benefits. Analysis of the samples and reference antioxidant (BHT) revealed a notable dose- dependent rise in free-radical-scavenging action, implying a positive concentration-dependent antioxidant efficacy. Variations in antioxidant activity occurred from tea wastes sourced at various factories, alluding to geography having a pivotal effect on the biological contents and antioxidative capacity. Of particular interest were Boito's and Chelal's cyclone fluff samples that evinced relatively lower potency than those from other factories. Tombe factory's cyclone sample demonstrated a superior capacity for scavenging free radicals at different concentrations, suggesting that particular production or cultivation processes augmented its effectiveness. Notably, some tea waste samples even equalled the potency of BHT (a synthetic antioxidant) when augured to its highest level. Furthermore, this study revealed disparities in Theaflavin and Thearubigin content due to factors like maturation period and processing methods guiding these concentrations. We identified tea waste samples possessing remarkable polyphenol concentration, thereby providing valuable insights for consumers and industries. Further investigations on the chemical composition of tea waste phytocompounds are paramount due to their acclaimed health-promoting properties and the factors influencing their concentrations and antioxidant efficacy.

MXene-modified lemon peel-based composite phase change material with excellent photo-thermal conversion efficiency, thermal storage capacity and thermal conductivity for thermal management of electronic components

The preparation of multifunctional composite phase change materials using green technology to achieve an efficient energy storage and conversion remains an issue of concern. In this paper, a lemon peel-based porous carbon (LPC) composite phase change material (CPCM) was prepared by using polyethylene glycol (PEG) 6000 as a phase change medium and MXene nanosheet-modified carbonized lemon peel as a support carrier. MXene nanosheets were bonded to a lemon peel-based porous carbon skeleton to construct an excellent continuous three-dimensional thermally conductive grid system. What makes it noteworthy is that the presence of MXene nanosheets substantially improves the thermal conductivity (0.66 W/mK) and photo-thermal conversion efficiency (θ = 96.4 %) of MXene-modified lemon peel-based porous carbon/polyethylene glycol composite phase change materials (PEG/LPC@M). It is noteworthy that PEG/LPC@M has remarkable thermal stability and still has high enthalpy after 100 cycles, which further proves the recyclability of PEG/LPC@M and PEG/LPC@M embodies great potential in the field of thermal management of electronic components. In conclusion, a novel multifunctional CPCM was prepared by a simple and green process method in this study, which provides a new idea for waste recycling and reuse, and also has a wide range of applications in thermal management of electronic devices.

Strawberry Detection and Ripeness Classification Using YOLOv8+ Model and Image Processing Method

Strawberry Detection and Ripeness Classification Using YOLOv8+ Model and Image Processing Method

Vocabulary Matters: An Annotation Pipeline and Four Deep Learning Algorithms for Enzyme Named Entity Recognition.

Enzymes are indispensable in many biological processes, and with biomedical literature growing exponentially, effective literature review becomes increasingly challenging. Natural language processing methods offer solutions to streamline this process. This study aims to develop an annotated enzyme corpus for training and evaluating enzyme named entity recognition (NER) models. A novel pipeline, combining dictionary matching and rule-based keyword searching, automatically annotated enzyme entities in >4800 full-text publications. Four deep learning NER models were created with different vocabularies (BioBERT/SciBERT) and architectures (BiLSTM/transformer) and evaluated on 526 manually annotated full-text publications. The annotation pipeline achieved an F1-score of 0.86 (precision = 1.00, recall = 0.76), surpassed by fine-tuned transformers for F1-score (BioBERT: 0.89, SciBERT: 0.88) and recall (0.86) with BiLSTM models having higher precision (0.94) than transformers (0.92). The annotation pipeline runs in seconds on standard laptops with almost perfect precision, but was outperformed by fine-tuned transformers in terms of F1-score and recall, demonstrating generalizability beyond the training data. In comparison, SciBERT-based models exhibited higher precision, and BioBERT-based models exhibited higher recall, highlighting the importance of vocabulary and architecture. These models, representing the first enzyme NER algorithms, enable more effective enzyme text mining and information extraction. Codes for automated annotation and model generation are available from https://github.com/omicsNLP/enzymeNER and https://zenodo.org/doi/10.5281/zenodo.10581586.

EFFECT OF PROCESSING METHODS ON NUTRIENT ANDANTINUTRIENT COMPOSITION OF JUSTICIA SECUNDA LEAVES

Justicia secunda as a medicinal plant belongs to the family of Acanthaceae ,the leaf is an under-utilized medicinal vegetable that is believed and utilized as blood tonic by the local people and especially among the sect of some religious people that refuse blood infusion in medical conditions. This study examined the effect of processing methods on the nutrient and phytochemical composition of justicia secunda leaves. The leaves were subjected to blanching pre-treatment before sun drying for 72 hrs oven drying at 55 0C for 48 hrs and air drying for 120 hrsThe proximate, vitamins, minerals and phytochemical analysis were conducted on the samples using standard procedures. The results varied significantly (p<0.05) in all the parameters measured according to the different processing treatments. Proximate composition of the samples ranged for crude protein (18.20-21.73%), crude fat (7.80-9.10%), crude fibre (12.00-14.90%), ash (15.50-17.40%), moisture (8.00-9.00%) and carbohydrate (27.98-35.50%). Mineral composition ranged for calcium (18.20-34.10 mg/100g), magnesium (47.11-54.29 mg/100g), sodium (126.43-136.47 mg/100g), potassium (425.49-453.03 mg/100g), phosphorus (135.40-145.76 mg/100g) and iron (33.07-38.94 mg/100g). Vitamin composition showed that thiamine (B1) ranged from 0.04-0.31 mg/100g, riboflavin (B2) (0.21-1.7 8mg/100g), niacin (B3) (0.49-1.89 mg/100g), vitamin C (6.31-19.48 mg/100g), while vitamin E ranged from (1.97-6.78 mg/100g). Anti-nutrient contents ranged for tannin (4.82-16.89 mg/100g), phenol (7.41-19.23 mg/100g), alkaloids (2.05-7.07 mg/100g) flavonoids (4.90-9.85 mg/100g) and saponin (3.25-8.35 mg/100g. Overall, the results revealed that air drying methods retained greater concentrations of fibre, minerals, vitamins and anti-nutrients than other processing methods. The high micro-nutrient contents of iron, anti-nutrient compounds and B group of vitamins in this processed vegetable reveals why it is used intuitively by the traditional people to boost health conditions due to the functional roles of iron, phytonutrients and B group of vitamins in heamopoisis in preventing morbidity and mortality especially among children.

Three-Dimensional Quality Assessment of Urban Underground Space Resource Based on Multiple Geological Environmental Factors

With the rapid advancement of urbanization, the development and utilization of urban underground space resource (UUSR) has become one of the dominant features. However, in certain areas, the development of UUSR may cause disasters and accidents, such as ground collapse, settlements, and tunnel water gushing. Geological environmental factors (GEFs) are recognized as the fundamental constraining factor of UUSR development. In this paper, quality based on GEFs is defined to assess the development difficulty degree of UUSR. A 3D assessment framework is proposed based on 3D geological modelling and the interval continuous mathematical model (ICMM). The subjective and objective joint weight method of analytic hierarchy process and entropy weight method (AHP–EWM) is utilized to determine the weight of each indicator. The quality index (QI) of each spatial node of the 3D geological model is calculated by the ICMM mathematical model. A case study conducted in the Jiangbei New District of Nanjing, China, serves as a demonstration of the UUSR assessment. The results clearly illustrate the 3D distribution characteristics of the quality in the study area, offering valuable insights for future 3D urban underground space planning.

Effectiveness Evaluation of Pyrometallurgy and Hydrometallurgy Methods in The Recycling Process of Nd-Fe-B Permanent Magnet and Rare Earth Metals Recovery : A Review

Effectiveness Evaluation of Pyrometallurgy and Hydrometallurgy Methods in The Recycling Process of Nd-Fe-B Permanent Magnet and Rare Earth Metals Recovery : A Review

Integrating fuzzy-AHP and GIS for solid waste disposal site selection in Kenitra province, NW Morocco.

Selecting an optimal solid waste disposal site is one of the decisive waste management issues because unsuitable sites cause serious environmental and public health problems. In Kenitra province, northwest Morocco, sustainable disposal sites have become a major challenge due to rapid urbanization and population growth. In addition, the existing disposal sites are traditional and inappropriate. The objective of this study is to suggest potential suitable disposal sites using fuzzy logic and analytical hierarchy process (fuzzy-AHP) method integrated with geographic information system (GIS) techniques. For this purpose, thirteen factors affecting the selection process were involved. The results showed that 5% of the studied area is considered extremely suitable and scattered in the central-eastern parts, while 9% is considered almost unsuitable and distributed in the northern and southern parts. Thereafter, these results were validated using the area under the curve (AUC) of the receiver operating characteristics (ROC). The AUC found was 57.1%, which is a moderate prediction's accuracy because the existing sites used in the validation's process were randomly selected. These results can assist relevant authorities and stakeholders for setting new solid waste disposal sites in Kenitra province.

LOLA DEM Assisted Photogrammetric Processing of Lunar Reconnaissance Orbiter NAC Images for the Lunar South Pole

Abstract. Because of its special significance, exploration missions and research at the Lunar South Pole (LSP) are of considerable importance. The mapping products of the LSP such as Digital Ortho Maps (DOMs) and Digital Elevation Models (DEMs) are essential to support exploration missions. However, in the LSP region, the available data are relatively limited. The large amounts of shadows and the special environment of the LSP has an important impact on both image matching and generation of mapping products. In this paper, we propose a photogrammetric processing method to improve the accuracy of the LRO NAC images by using LOLA DEM as auxiliary control data. The LOLA DEM was first rendered using the same illumination conditions as the corresponding LRO NAC raw images, and then matched to the LRO NAC DOMs. Next, the corresponding elevations of the tie points between LOLA DEMs and LRO NAC images were extracted and automatically added to the control network for bundle adjustment. In order to verify the feasibility of the method, we selected 17 LRO NAC images near the LSP at 85° south latitude. The results show that the proposed method can efficiently acquire uniformly distributed elevation control points for bundle adjustment and the generated DEM has a good consistency with the LOLA DEM.

Feature selection algorithm based on optimized genetic algorithm and the application in high-dimensional data processing

High-dimensional data is widely used in many fields, but selecting key features from it is challenging. Feature selection can reduce data dimensionality and weaken noise interference, thereby improving model efficiency and enhancing model interpretability. In order to improve the efficiency and accuracy of high-dimensional data processing, a feature selection method based on optimized genetic algorithm is proposed in this study. The algorithm simulates the process of natural selection, searches for possible subsets of feature, and finds the subsets of feature that optimizes the performance of the model. The results show that when the value of K is less than 4 or more than 8, the recognition rate is very low. After adaptive bias filtering, 724 features are filtered to 372, and the accuracy is improved from 0.9352 to 0.9815. From 714 features to 406 Gaussian codes, the accuracy is improved from 0.9625 to 0.9754. Among all tests, the colon has the highest average accuracy, followed by small round blue cell tumor(SRBCT), lymphoma, central nervous system(CNS) and ovaries. The green curve is the best, with stable performance and a time range of 0–300. While maintaining the efficiency, it can reach 4.48 as soon as possible. The feature selection method has practical significance for high-dimensional data processing, improves the efficiency and accuracy of data processing, and provides an effective new method for high-dimensional data processing.

A case of mistaken identity: a systematic review, meta-analysis, and reinvestigation of hemotropic Mycoplasma spp. infection in Ctenocephalides felis (cat flea)

Background Feline-associated hemotropic Mycoplasma (hemoplasmas) are believed to be transmitted by two primary mechanisms: (1) direct transmission via fighting and (2) vector-borne transmission by the cat flea (Ctenocephalides felis). While the efficiency of transmission by C. felis appears low, most manuscripts focus on the prevalence of hemoplasmas in wild-caught fleas and report either a very low (< 3%) or a high (> 26%) prevalence. Therefore, we aimed to assess the influence of sample processing and PCR methods on C. felis hemoplasma infection prevalence. MethodsA systemic review of PubMed articles identified 13 manuscripts (1,531 fleas/flea pools) that met the inclusion criteria (performed PCR for >1 hemoplasma on C. felis collected from cats). Risk of bias was assessed utilizing the ROBINS-E tool. Meta-analysis performed in R of these manuscripts found that not washing samples and a common set of 16S rRNA primers first published in Jensen et al. 2001 were associated with increased hemoplasma prevalence. To evaluate the influence of washing on newly collected fleas, we assessed the hemoplasma status of 20 pools of 5 C. felis each, half of which were washed and half not washed.ResultsFlea washing did not influence the detection of hemoplasma but instead amplified Spiroplasma. To assess non-specific amplification with the Jensen et al. 2001 primers, 67 C. felis samples (34% previously reported hemoplasma infected) were subject to PCR and sequencing. By this method, hemoplasma was detected in only 3% of samples. In the remaining “hemoplasma infected” fleas, PCR amplified Spiroplasma or other bacteria. ConclusionsTherefore, we concluded that hemoplasma infection in C. felis is rare, and future flea prevalence studies should sequence all positive amplicons to validate PCR specificity. Further investigation of alternative methods of feline-associated hemoplasma transmission and the ability of C. felis to maintain hemoplasma infection is necessary.Graphical

Combining statistical dialog management and intent recognition for enhanced response selection

Abstract Conversational interfaces are becoming ubiquitous in an increasing number of application domains as Artificial Intelligence, Natural Language Processing and Machine Learning methods associated with the recognition, understanding and generation of natural language advance by leaps and bounds. However, designing the dialog model of these systems is still a very demanding task requiring a great deal of effort given the number of information sources to be considered related to the analysis of user utterances, interaction context, information repositories, etc. In this paper, we present a general framework for increasing the quality of the system responses by combining a statistical dialog management technique and a deep learning-based intention recognizer that allow replacing the system responses initially selected by the statistical dialog model with other presumably better candidates. This approach is portable to different task-oriented domains, a diversity of methodologies for dialog management and intention estimation techniques. We have evaluated our two-step proposal using two conversational systems, assessed several intention recognition methodologies and used the developed modules to dynamically select the system responses. The results of the evaluation show that the proposed framework achieves satisfactory results by making it possible to reduce the number of non-coherent dialog responses by replacing them by more coherent alternatives.

Small sample uncertainty evaluation of industrial robot position accuracy measurement based on grey model

The measurement of position accuracy of industrial robots has high complexity, and its uncertainty assessment is one of the important research topics. This study analyses the principle of measuring the position accuracy of industrial robots by laser tracker, the evaluation model of the measurement uncertainty of the position accuracy of industrial robots is established, and various factors affecting the measurement results are analysed, including industrial robot itself, the measurement instrument, the measurement personnel, the measurement strategy and the data processing method. There is a very small sample problem in the uncertainty evaluation process of the position accuracy of industrial robots. The literature and experiments show that the reliability of The Guide to the Expression of Uncertainty in Measurement is low under the condition of very small sample. In this study, an improved grey method is proposed to evaluate the uncertainty. The principle of the improved grey method is discussed in detail, and the general steps of the improved grey method are summarized. The experimental data prove that the standard deviation of very small sample calculated by the improved grey method has higher accuracy. Taking the position accuracy of an industrial robot measured by a laser tracker as an example, the improved grey method is successfully applied to the measurement uncertainty evaluation of the position accuracy of industrial robots.

Robust and Superhydrophobic Polydimethylsiloxane/Ni@Ti3C2Tx Nanocomposite Coatings with Assembled Eyelash-Like Microstructure Array: A New Approach for Effective Passive Anti-Icing and Active Photothermal Deicing.

To solve the problem of ice condensation and adhesion, it is urgent to develop new anti-icing and deicing technologies. This study presented the development of a highly efficient photothermal-enhanced superhydrophobic PDMS/Ni@Ti3C2Tx composite film (m-NMPA) fabricated cost-effectively and straightforwardly. This film was fabricated utilizing PDMS as a hydrophobic agent, adhesive, and surface protector, while Ni@Ti3C2Tx as a magnetic photothermal filler innovatively. Through a simple spraying method, the filler is guided by a strong magnetic field to self-assemble into an eyelash-like microstructure array. The unique structure not only imparts superhydrophobic properties to the surface but also constructs an efficient "light-capturing" architecture. Remarkably, the m-NMPA film demonstrates outstanding superhydrophobic passive anti-icing and efficient photothermal active deicing performance without the use of fluorinated chemicals. The micro-/nanostructure of the film forms a gas layer, significantly delaying the freezing time of water. Particularly under extreme cold conditions (-30 °C), the freezing time is extended by a factor of 7.3 compared to the bare substrate. Furthermore, under sunlight exposure, surface droplets do not freeze. The excellent photothermal performance is attributed to the firm anchoring of nickel particles on the MXene surface, facilitating effective "point-to-face" photothermal synergy. The eyelash-like microarray structure enhances light-capturing capability, resulting in a high light absorption rate of 98%. Furthermore, the microstructure aids in maintaining heat at the uppermost layer of the surface, maximizing the utilization of thermal energy for ice melting and frost thawing. Under solar irradiation, the m-NMPA film can rapidly melt approximately a 4 mm thick ice layer within 558 s and expel the melted water promptly, reducing the risk of secondary icing. Additionally, the ice adhesion force on the surface of the m-NMPA film is remarkably low, with an adhesion strength of approximately 4.7 kPa for a 1 × 1 cm2 ice column. After undergoing rigorous durability tests, including xenon lamp weathering test, pressure resistance test, repeated adhesive tape testing, xenon lamp irradiation, water drop impact testing, and repeated brushing with hydrochloric acid and particles, the film's surface structure and superhydrophobic performance have remained exceptional. The photothermal superhydrophobic passive anti-icing and active deicing technology in this work rely on sustainable solar energy for efficient heat generation. It presents broad prospects for practical applications with advantages such as simple processing method, environmental friendliness, outstanding anti-icing effects, and exceptional durability.

TKO‐SLAM: Visual SLAM algorithm based on time‐delay feature regression and keyframe pose optimization

AbstractThis paper addresses the challenge of generating clear image frames and minimizing the loss of keyframes by a robot engaging in rapid large viewing angle motion. These issues often lead to detrimental consequences such as trajectory drifting and loss during the construction of curved motion trajectories. To tackle this, we proposed a novel visual simultaneous localization and mapping (SLAM) algorithm, TKO‐SLAM, which is based on time‐delay feature regression and keyframe position optimization. TKO‐SLAM uses a multiscale recurrent neural network to rectify object deformation and image motion smear. This network effectively repairs the time‐delay image features caused by the rapid movement of the robot, thereby enhancing visual clarity. Simultaneously, inspired by the keyframe selection strategy of the ORB‐SLAM3 algorithm, we introduced a grayscale motion‐based image processing method to supplement keyframes that may be omitted due to the robot's rapid large viewing angle motion. To further refine the algorithm, the time‐delay feature regression image keyframes and adjacent secondary keyframes were used as dual measurement constraints to optimize camera poses and restore robot trajectories. The results of experiments on the benchmark RGB‐D data set TUM and real‐world scenarios show that TKO‐SLAM algorithm achieves more than 10% better localization accuracy than the PKS‐SLAM algorithm in the rapid large viewing angle motion scenario, and has advantages over the SOTA algorithms.

THE PROBLEM OF REGULATING FUNGICIDES ON THE SKIN SURFACE FOR OCCUPATIONAL SKIN DISEASE IN AGRICULTURAL WORKERS’ RISK PREDICTION

The aim. To establish the norms of fungicides on the skin surface and predicting the risk of occupational skin pathology in agricultural workers to develop measures to prevent diseases caused by dermal exposure to pesticides. Materials and methods. The natural experiment was performed in accordance with modern requirements (European Food Safety Authority (2022), and the risk assessment was carried out according to the Recommendations (Approved by the Ministry of Health of Ukraine No. 324 issued on 13.05.2009) with different methods of spraying techniques: rod, air blast fan spraying, pre-sowing, aviation, knapsack treatment. 17 series of natural experiments were performed, and the air of the working zone area (n =56) and dermal exposure (n =56) were analyzed for each worker with different pesticide application methods. Quantitative determination of pesticide content was carried out by gas-liquid and high-performance liquid chromatography methods. The results were statistically processed using a package of licensed statistical programs MedStat v.5.2 (Copyright © 2003-2019) and Microsoft® Excel® for Microsoft 365 MSO. Results. It was established that there is pesticide contamination, mainly of the gloves of tank filling operators when preparing working solutions. No contamination of the skin surface was detected; only pesticide residues were present on the surface of the workers’ overalls. A comparison of the exposure dose in case of percutaneous exposure during the performance of technological operations with different methods of processing, dermal equivalents of Acceptable Operator Exposure Level of pesticide to workers’ skin (DE AOEL) and the allowable dermal dose for professional contingents (ADderm) and the hazard coefficients by dermal exposure (HCderm) showed that that dermal exposure during individual technological operations with different processing methods had a reliable difference between processing methods, but there is no difference within one application method. Conclusions. During the comparison of the hazard coefficients for dermal exposure, calculated according to different models, no significant difference was found between the risks calculated according to DE AOEL and ADderm for individual technological operations in various treatment methods, except for the operator who performed knapsack treatment and the risk calculated according to ADderm is significantly lower compared to the DE AOEL risk.

Rhythm-adaptive statistical estimation methods of probabilistic characteristics of cyclic random processes

The paper is devoted to the rhythm-adaptive statistical estimation methods of cyclic random processes probabilistic characteristics. The main goal of the article is development and research of rhythm-adaptive methods of cyclic random processes statistical processing. Based on the fundamental fact of invariance of probabilistic characteristics of a cyclic random process to time shifts determined by its rhythm function, rhythm-adaptive statistical estimations of initial, central and mixed moment functions of cyclic random processes of discrete parameter were obtained. The article analytically proves the unbiasedness and consistency of rhythm-adaptive statistical estimates of the mathematical expectation and the initial moment functions of the higher order of cyclic random process. By conducting a series of computer simulation experiments, it has been demonstrated, that the absolute errors of rhythm-adaptive methods of statistical estimation are significantly smaller than the corresponding errors for classical non-rhythm adaptive methods of statistical estimation of cyclic stochastic signals probabilistic characteristics. The effectiveness of using rhythm-adaptive methods of statistical estimation of probabilistic characteristics of ECG signals has been demonstrated. The results obtained in the work clearly demonstrate the essential advantages of rhythm-adaptive methods of statistical processing of cyclic stochastic signals with a variable (irregular) rhythm in comparison with non-rhythm-adaptive analogues.

Analysis of Ethnopharmaceutical Studies of Traditional Medicine for the Management of Jaundice Due to Hepatic Disorders by the Mandar Tribe of West Sulawesi, Indonesia

Jaundice, or icterus, is a medical condition characterized by yellowing of the skin and whites of the eyes. This is caused by a buildup of bilirubin in the blood, which is a waste product of the breakdown of red blood cells. Liver disorders, such as hepatitis, are the most common cause of jaundice. The Mandar tribe in West Sulawesi Indonesia has a traditional healing tradition that has been passed down from generation to generation. This traditional medicine is often used to treat various diseases, including jaundice. This study aims to analyze the ethnopharmaceutical traditional treatment for jaundice in the Mandar tribe in West Sulawesi. This research used a descriptive observational method with traditional healthcare respondents. Data was collected through interviews and observations of traditional healers and patients who used traditional medicine. The data was analyzed descriptively to determine the type of plant, part of the plant used, processing methods, and how traditional medicines are used. This research found 14 plant species from 13 families that were used as medicine for jaundice. Two types of plants are typically used by the Mandar tribe, namely lapo-lapo (Melanolepis multiglandulosa) and barorang (Blumea balsamifera). The parts of the plant most commonly used as medicine are leaves (43%), followed by fruit (29%), stems (14%), roots (7%), rhizomes (4%), and herbs (3%). Plant processing by pressing and boiling is the most widely used (50% each). The most common method of use is boiling (70%), followed by pounding (20%) and eating directly (10%). This research found 14 plant species from 13 families that were used by the Mandar tribe as medicine for jaundice. Two types of plants are typically used, namely lapo-lapo and barorang. This research provides important information about the Mandar tribe's ethnopharmacology for jaundice and can be a basis for the development of more effective and safer traditional medicines.