FORMULATION AND EVALUATION OF WOUND HEALING GEL OF WHITE LEADTREE (LEUCAENA LEUCOCEPHALA (LAM.) DE WIT.) LEAVES EXTRACT

Objective: The aim of this research is to formulate and evaluate the wound healing gel of Leucaena leucocephala leaves extract. Methods: In this research, the extract of Leucaena leaves was formulated into wound healing gel by using a variation of the concentration of Carbopol as a gelling agent and Propylene glycol as a humectant. Afterward, the gel's physical properties (pH, viscosity, spreadability), stability, and sterility were tested. The wound healing activity was evaluated by making excision wounds on the Wistar Albino rat's back, and then the gels were applied to the wound every day. The wound's size was measured and counted as the percentage of wound closure. Results: The result showed that Formula 4 (contains 1.5% of Carbopol and 12% of Propylene glycol) has the best physical characteristics and wound healing activity. Formula 4 showed 100% wound closure on the 11th day of the treatment, while the negative control only reached 49.12%. The statistical parameter with the p-value<0.05 stated that they are significantly different. Conclusion: This research demonstrated that gel with Leucaena leaf extract has good physical characteristics, and it can significantly improve the wound healing process.

Localizing Epileptic Foci Before Surgery in Patients With MRI-Negative Refractory Epilepsy Using Statistical Parameter Mapping and Three-Dimensional Stereotactic Surface Projection Based on 18F-FDG PET

Patients with refractory epilepsy are not only free of seizures after resecting epileptic foci, but also experience significantly improved quality of life. Fluorine-18-fluorodeoxyglucose positron-emission tomography (18F-FDG PET) is a promising avenue for detecting epileptic foci in patients with magnetic resonance imaging (MRI)-negative refractory epilepsy. However, the detection of epileptic foci by visual assessment based on 18F-FDG PET is often complicated by a variety of factors in clinical practice. Easy imaging methods based on 18F-FDG PET images, such as statistical parameter mapping (SPM) and three-dimensional stereotactic surface projection (3D-SSP), can objectively detect epileptic foci. In this study, the regions of surgical resection of patients with over 1 year follow-up and no seizures were defined as standard epileptic foci. We retrospectively analyzed the sensitivity of visual assessment, SPM and 3D-SSP based on 18F-FDG PET to detect epileptic foci in MRI-negative refractory epilepsy patients and obtained the sensitivities of visual assessment, SPM and 3D-SSP are 57, 70 and 60% respectively. Visual assessment combined with SPM or 3D-SSP can improve the sensitivity of detecting epileptic foci. The sensitivity was highest when the three methods were combined, but decreased consistency, in localizing epileptic foci. We conclude that SPM and 3D-SSP can be used as objective methods to detect epileptic foci before surgery in patients with MRI-negative refractory epilepsy. Visual assessment is the preferred method for PET image analysis in MRI-negative refractory epilepsy. When the visual assessment is inconsistent with the patient’s electroclinical information, SPM or 3D-SSP was further selected to assess the epileptic foci. If the combination of the two methods still fails to accurately locate the epileptic foci, comprehensive evaluation can be performed by combining the three methods.

Interstellar Neutral He Parameters from Crossing Parameter Tubes with the Interstellar Mapping and Acceleration Probe Informed by 10 yr of Interstellar Boundary Explorer Observations

The Sun's motion through the interstellar medium leads to an interstellar neutral (ISN) wind through the heliosphere. Several ISN species, including He, moderately depleted by ionization are observed with pickup ions and directly imaged. Since 2009, analyzed Interstellar Boundary Explorer (IBEX) observations returned a precise 4D parameter tube associated with the bulk velocity vector and the temperature of ISN flow distribution. This 4D parameter tube is typically expressed in terms of the ISN speed, the inflow latitudinal direction, and the temperature as a function of the inflow longitudinal direction and the local flow Mach number. We have used IBEX observations and those from other spacecraft to reduce statistical parameter uncertainties: V ISN ∞ = 25.99 ± 0.18 km s−1, λ ISN ∞ = 75 .° 28 ± 0 .° 13 , β ISN ∞ = −5 .° 200 ± 0 .° 075 , and T ISN ∞ = 7496 ± 172 K. IBEX ISN viewing is restricted almost perpendicular to the Earth–Sun line, which limits observations in ecliptic longitude to ∼130° ± 30° and results in relatively small uncertainties across the IBEX parameter tube but large uncertainties along it. Operations over the last three years enabled the IBEX spin axis to drift to the maximum operational offset (7°) west of the Sun, helping to break the ISN parameter degeneracy by weakly crossing the IBEX parameter tubes: the range of possible inflow longitudes extends over the range λ ISN ∞ = 75 .° 28 − 2.21 + 2.27 and the corresponding range of other ISN parameters is V ISN ∞ = 25.99 − 1.76 + 1.86 km s−1, β ISN ∞ = −5 .° 200 − 0.085 + 0.093 , and T ISN ∞ = 7496 − 1528 + 1274 K. This enhances the full χ 2 analysis of ISN parameters through comparison with detailed models. The next-generation IBEX-Lo sensor on IMAP will be mounted on a pivot platform, enabling IMAP-Lo to follow the ISN flow over almost the entire spacecraft orbit around the Sun. A near-continuous set of 4D parameter tube orientations on IMAP will be observed for He and for O, Ne, and H that cross at varying angles to substantially reduce the ISN flow parameter uncertainties and mitigate systematic uncertainties (e.g., from ionization effects and the presence of secondary components) to derive the precise parameters of the primary and secondary local interstellar plasma flows.

STATUS KEBERLANJUTAN PENGELOLAAN EKOSISTEM MANGROVE DI KECAMATAN TARUMAJAYA, KABUPATEN BEKASI

Mangrove ecosystems provide various useful types of products and services to support the life needs of coastal communities. In the management of sustainable mangrove ecosystems, it is necessary to integrate activities in the ecological, economic, and social dimensions as it is known in the concept of sustainable development. This study aims to measure the sustainability status of mangrove ecosystem management in Tarumajaya District, Bekasi Regency. Data analysis is applying RAPFISH with the multidimensional scaling (MDS) method. The results show that the sustainability status of mangrove ecosystem management in Tarumajaya District, Bekasi Regency, obtains a multidimensional index value of 45.79% with less sustainable status, index value; and the sustainability status in each dimension, is 21.72% for the ecological dimension (unsustainable), 49.15% for economic dimension (less sustainable), 40.68 % for social dimension (less sustainable), and 63.68% for institutional dimension (quite sustainable). The influencing factors for the sustainability of mangrove ecosystem management consist of 16 indicators from the 4 dimensions tested. The results of statistical parameter validation and the results of the Monte Carlo test show that all of the dimension indicators analyzed in the management of sustainability of mangrove ecosystems have a significant role in explaining the diversity of mangrove ecosystems dimensional index value and have a high level of confidence.

Difference in clinical profile between juvenile onset and adult-onset systemic lupus erythematosus: a meta-analysis

The aim was to systematically review the studies that compared clinical and serological variation between adult-onset systematic lupus erythematosus (aSLE) andjuvenile-onset systematic lupus erythematosus (jSLE). A comprehensive literature search was done, in various available electronic databases for relevant publication that compared juvenile onset SLE and adult onset SLE. The data of adverse clinical features, serological profile and mortality were extracted. Juvenile onset was defined as <18 years and adult onset was defined as >18 years. The methodological quality of study was assessed by Newcastle Ottawa scale (NOS) criteria and R version 3.3.1 was used for analysis and ORs and 95% CIs, were used as statistical parameter. A total of 14,920 patients; (12,230: aSLE, and 2,690: jSLE) were included. Renal involvement especially nephritis was significantly more in j-SLE OR: 2.18, 95% CI: [1.81;2.62]; I2=10.8% whereas musculoskeletal was significant in aSLE O.R: 0.64; C.I: [0.44; 0.93]; I2=83.4%. Seizure and malar rash were significantly higher in J-SLE OR:1.69, CI: [1.31; 2.18]; I2=31.1%,1.43; C.I [1.04; 1.97]; I2=82%, respectively. Raynaud’s phenomenon and pleuritis were significantly higher in adult onset SLE. Anemia and thrombocytopenia were significantly higher in juvenile onset SLE. Anti-ds DNA, anti-histone, and anti-ribosomal-P were more frequent in juvenile-onset SLE while, anti-Ro was more common in adult-onset disease. The cause of mortality was not significantly different in both groups. Renal biopsy of class III and IV combined and class V were significantly more in adult-onset SLE. SLEDAI was higher in j-SLE. Meta-analysis indicated that, regardless of many similar clinical and serological manifestations, there is still some variation between adult-onset SLE and juvenile-onset SLE. Although, SLE disease is continuum from juvenile to adult but disease aggressive in juvenile onset SLE.

SWAT Application for Gajahwong River Streamflow Simulation

Gadjahwong River flows along Daerah Istimewa Yogyakarta (DIY) that is located in southern Java Island. Gadjahwong River has an important role for water supply purpose especially for agriculture activities. On the other hand, DIY is seeing 1.18% population growth each year. The population surge influences land cover change that can seize continuous discharge of Gadjahwong River. Therefore, continuous discharge simulation needs to be conducted for assessing Gadjahwong River water availability. Soil and Water Assessment Tool (SWAT) was employed for modelling Gadjahwong River streamflow discharge. The simulation result discharge was compared with observed data acquired at AWLR Wonokromo by using NSE and R2 statistical parameter. Finally, the statistical parameter was applied to justify quality of simulation. Findings showed that daily time step yielded NSE value of 0.61, R2 value of 0.79, and PBIAS value of -2.41%. Overall, the simulation showed good result based the statistical parameters.

Ultrasonic Pretreatment-Assisted Electrohydrodynamic Drying of Potato Slices

To investigate the drying characteristics and mechanism during electrohydrodynamic (EHD) drying with ultrasonic pretreatment, the ultrasonic pretreatment-assisted EHD drying method at different power values was used to carry out the drying experiment of potatoes. To carry out this study, potato slices were pretreated with different ultrasonic power values (150, 180, 210, 240, and 270 W) or without ultrasound for 30 min at 30°C. The corresponding voltage was 18 kV during EHD drying. The moisture ratio, drying rate, color, shrinkage, and rehydration rate of potatoes were determined. The microstructure of potatoes was analyzed using infrared spectroscopy and scanning electron microscopy. Eight mathematical models were used to fit the drying of potatoes. Results showed that, compared with the control group, the ultrasonic pretreatment combined with the EHD drying group had improved the drying rate of potato slices, which was different at varying ultrasonic power values. Ultrasonic pretreatment had a remarkable effect on the color of the potato but had little effect on the shrinkage rate. The maximum rehydration rate is 5.7704 at 180 W. The minimum and maximum values of effective moisture diffusivity (Deff) were 3.4070 × 10−7 m2/s and 4.1160 × 10−7 m2/s, respectively. The effect of ultrasonic power pretreatment on the microstructure of potato in the EHD drying process was significant ( p > 0.05 ). According to the statistical parameter evaluation, eight mathematical models could satisfactorily describe drying curves of potato slices dried under EHD with ultrasonic pretreatment, and the logarithmic model was best suited. This work provides a theoretical basis and practical guidance to further understand the parameter characteristics and mechanism of ultrasonic pretreatment combined with the EHD drying technology.

Elaboration of forecasting methods of analysis of metallurgical facilities electric drives technical state

To prevent losses of equipment downtime, analytical algorithms and data of automated control systems sensors are used to estimate time to the equipment failure approach. It was shown that modern technical systems, such as automated electric drives are equipped by measuring devices which allow to accomplish self-diagnostic of the system in real time mode at existing methods of data processing and analysis. This approach is more effective than traditional methods of diagnostic and does not include additional capital expenses for specialized diagnostic equipment and personal qualification. Hypothesis of forecasting of electromechanical driving system state was elaborated and checked for continuous rolling mill runaway roller, based on character of loading modes by using only one parameter – the electric motor current. Based on the data analysis of wide strip rolling mill 2000 runaway rollers operation, normalized curves of distribution of average values of the runaway roller drive current at its normal operation and origination of a malfunction were built. It was shown that a technical system state change is fixed at appearance of a deviation of load current distribution comparing with a standard deviation. Analysis of dynamics of a statistical parameter, the standard error (the difference between actual and standard distribution) at a transition process allowed to make a forecast of roller jamming several days before the malfunction took place. The proposed approach of equipment state estimation can become a base for elaboration of a principally new methods of diagnostic of metallurgical rotor equipment.

Machine Learning based Self-sensing the Stiffness of Shape Memory Coil Actuator

Self-sensing actuation (SSA) assists in sensing the vital property of the shape memory coil which can be used to monitor and control the actuation. The stiffness characteristic of the shape memory coil is sensed during actuation which plays a significant role in development of Intelligent Robotics in defense systems. The electrical property of shape memory coil such as electrical resistance changes due to martensitic phase transformation which is further used to sense the mechanical properties such as strain, stress, temperature, length, and force. Nowadays electrical properties are used to sense the stiffness of the shape memory coil. As of now, there is no well-established analytical model to predict the stiffness of sensing during actuation accurately. Therefore, Machine Learning (ML) based data-driven intelligent model is proposed in this paper for auto-sensing of the stiffness. The experimental facility has been developed for the collection of data with respect to diverse Joule heating currents. To determine the experimental data values of stiffness and electrical resistance of shape memory coil is a cumbersome task. Hence we have proposed an automated method to predict the stiffness of the shape memory coil using ML methods. The Classical Polynomial and Feedforward Neural Network (FFNN) models are developed for analyzing the stiffness of the shape memory coil. It is found that FFNN model outperforms the other ML based model by attaining 95.2650 % accuracy. The FFNN model is also able to explain almost all the predicted stiffness values which are experimentally recorded. The FVU (Fraction Variance Unexplained) statistical parameter explains the prediction of FFNN with the value of 0.0842. The great advantage of the ML model is to replace two sensors (Force and displacement sensors) with one soft sensor (ML model). It will be useful in the controlling robotics and other devices which require high precision in data generated by the sensors.