Good Model Research Articles

Development of Makassar City's Service Model and Transportation for Goods and Passengers

A well-thought-out, well-integrated operator of freight and passenger transportation with a wide clientele that can benefit both the service users and the overall framework of the transportation system. In this study, Makassar City's freight and passenger transportation services are modeled as urban transportation. In order to develop an integrated service model, this kind of research uses qualitative data that is then theoretically examined. According to the study's findings, using the Tallo River as a transportation route will improve the performance of goods and passenger transportation services while reducing road load. According to research, this model can affect how much traffic there is on the road, how quickly services are provided, how much it costs, and how each place the transportation system travels through develops.

Optimizing dialysis water treatment based on medical planning requirements

This paper introduces a new approach to improving hemodialysis and peritoneal dialysis processes. This maintains compatibility between the water treatment unit and active dialysis machines. Identification of different deviations in the patient’s requirements to classify the suitable flow rate (FR) of the pure water can be created through an Adaptive Neuro-Fuzzy Inference System (ANFIS). Four types of categories are classified: quarter load, half load, three-quarter load, and full load. This includes two main steps: identifying the dialysis categories with patients and measuring the suitable FR for each category. The effective FR of water was computed to indicate how the number of pumps rose as the number of patients treated within the dialysis unit increased. The introduced prediction method was tested against artificial neural networks to predict alum doses (ANN-AD) method, artificial intelligence as a combinatorial optimization strategy (AN-COS) using peach-palm waste in a solid-state fermentation environment, expert system applications (ESA) in chronic kidney disease management (MDSSs), prescription optimization for automated peritoneal dialysis (BCPH). In this work, pumping system parameter estimation was utilized to assess the performance of the introduced systems based on input voltage, input current, rotor speed, and electromagnetic torque waveforms of the pumping drive. This method uses the ANFIS algorithm to construct a high-performance pumping system to evaluate and predict the flow rate of dialysis machines based on input–output estimates. The flow rate values for each patient in critical care units can be controlled by the presented algorithm according to the time of dialysis. A good predictive model based on integrating the experience and decision making of medical planners was implemented. The proposed method not only improves accuracy but also saves time in the dialysis unit. The presented fuzzy classifier uses the ratio of the number of predicted true positives and false positives to the total number of anticipated positives. The simulation results show that the proposed technique can be successfully used to classify the suitable FR of the water according to the hemodialysis load. One of the advantages of the presented technique is the ability to predict the value of FR in real time with reliability, low computational complexity, and a high accuracy of 98.01%, which simplifies the dialysis process for many patients while at the same time leading to improved performance of hemodialysis. The presented method can be implanted in online FR estimation and analysis hardware for hemodialysis, is easy to calculate and run in real time, minimizes hemodialysis costs, and saves run time.

Drosophila models of phosphatidylinositol glycan biosynthesis class A congenital disorder of glycosylation (PIGA-CDG) mirror patient phenotypes.

Mutations in the phosphatidylinositol glycan biosynthesis class A (PIGA) gene cause a rare, X-linked recessive congenital disorder of glycosylation. Phosphatidylinositol glycan biosynthesis class A congenital disorder of glycosylation (PIGA-CDG) is characterized by seizures, intellectual and developmental delay, and congenital malformations. The PIGA gene encodes an enzyme involved in the first step of glycosylphosphatidylinositol (GPI) anchor biosynthesis. There are over 100 GPI-anchored proteins that attach to the cell surface and are involved in cell signaling, immunity, and adhesion. Little is known about the pathophysiology of PIGA-CDG. Here, we describe the first Drosophila model of PIGA-CDG and demonstrate that loss of PIG-A function in Drosophila accurately models the human disease. As expected, complete loss of PIG-A function is larval lethal. Heterozygous null animals appear healthy but, when challenged, have a seizure phenotype similar to what is observed in patients. To identify the cell-type specific contributions to disease, we generated neuron- and glia-specific knockdown of PIG-A. Neuron-specific knockdown resulted in reduced lifespan and a number of neurological phenotypes but no seizure phenotype. Glia-knockdown also reduced lifespan and, notably, resulted in a very strong seizure phenotype. RNA sequencing analyses demonstrated that there are fundamentally different molecular processes that are disrupted when PIG-A function is eliminated in different cell types. In particular, loss of PIG-A in neurons resulted in upregulation of glycolysis, but loss of PIG-A in glia resulted in upregulation of protein translation machinery. Here, we demonstrate that Drosophila is a good model of PIGA-CDG and provide new data resources for future study of PIGA-CDG and other GPI anchor disorders.

Predicting outcome in acute stroke with large vessel occlusion-application and validation of MR PREDICTS in the ESCAPE-NA1 population.

Predicting outcome after endovascular treatment for acute ischemic stroke is challenging. We aim to investigate differences between predicted and observed outcomes in patients with acute ischemic stroke treated with endovascular treatment and to evaluate the performance of a validated outcome prediction score. MR PREDICTS is an outcome prediction tool based on a logistic regression model designed to predict the treatment benefit of endovascular treatment based on the MR CLEAN and HERMES populations. ESCAPE-NA1 is a randomized trial of nerinetide vs. placebo in patients with acute stroke and large vessel occlusion. We applied MR PREDICTS to patients in the control arm of ESCAPE-NA1. Model performance was assessed by calculating its discriminative ability and calibration. Overall, 556/1105 patients (50.3%) in the ESCAPE-NA1-trial were randomized to the control arm, 435/556 (78.2%) were treated within 6 h of symptom onset. Good outcome (modified Rankin scale 0-2) at 3 months was achieved in 275/435 patients (63.2%), the predicted probability of good outcome was 52.5%. Baseline characteristics were similar in the study and model derivation cohort except for age (ESCAPE-NA1: mean: 70 y vs. HERMES: 66 y), hypertension (72% vs. 57%), and collaterals (good collaterals, 15% vs. 44%). Compared to HERMES we observed higher rates of successful reperfusion (TICI 2b-3, ESCAPE-NA1: 87% vs. HERMES: 71%) and faster times from symptom onset to reperfusion (median: 201 min vs. 286 min). Model performance was good, indicated by a c-statistic of 0.76 (95%confidence interval: 0.71-0.81). Outcome-prediction using models created from HERMES data, based on information available in the emergency department underestimated the actual outcome in patients with acute ischemic stroke and large vessel occlusion receiving endovascular treatment despite overall good model performance, which might be explained by differences in quality of and time to reperfusion. These findings underline the importance of timely and successful reperfusion for functional outcomes in acute stroke patients.

Dimensionality of Speech-Language Pathologists' Child-Directed Talk During School-Based Therapy With Primary-Grade Students.

The purpose of this study was to examine the measurement structure of the linguistic features of speech-language pathologists' (SLPs) talk during business-as-usual therapy sessions in the public schools and to test the longitudinal stability of a theorized dimensional structure consisting of quantity, grammatical complexity, and lexical complexity. Seventy-five SLPs' talk during therapy sessions with primary-grade students was automatically transcribed and coded for linguistic features from a corpus of 579 videotaped therapy session videos collected at the beginning, middle, and end of one school year with an approximately 12-week interval. We explored video characteristics and conducted descriptive statistics on eight linguistic indices of SLP talk to examine the variability in SLP talk between therapy sessions. Confirmatory factor analyses were used to explore the dimensional structure of SLP talk at each time point separately for the theorized three dimensions, and we conducted longitudinal measurement invariance analyses to test the stability of the three-factor structural model across the academic year. There were considerable variabilities among SLPs in the characteristics of SLP talk during therapy sessions. The proposed three-factor structure of SLP talk consisting of quantity, grammatical complexity, and lexical complexity had good model fit at all three time points. The linguistic measurement properties representing the three factors were invariant over time. Results provided robust evidence of between-SLP variability in their child-directed talk, established a three-dimensional structure of the linguistic features in SLP talk, and identified that the linguistic features in SLP talk stably measured the same constructs across one school year, based on measurement invariance. The dimensions of SLP talk during therapy with students may represent important, malleable features of therapy that influence child language gains.

A Channel Financing Policy for an EOQ Model of Fast-Moving Consumer Goods with Fuzzy Approach

A Channel Financing Policy for an EOQ Model of Fast-Moving Consumer Goods with Fuzzy Approach

Exploring Secondary School Principals’ Experiences and Leadership Practices in Building Professional Learning Communities: A Case Study in Klang, Malaysia

<p style="text-align: justify;">A study showed Malaysian students were unable to achieve the minimum standards in Mathematics and Science subjects, prompting the need for educational reformation. With this, educators need to inculcate Professional Learning Community (PLC) to enhance the teaching quality. This study explores secondary school principals’ PLC practices and experiences to improve student achievement in Klang, Malaysia. The qualitative case study was conducted using randomly selected two secondary school principals in Klang. The interview session comprised four interview questions and was conducted via an online platform. The results showed two common PLC practices which are annual meetings and observation. The challenges faced by school principals to implement PLC were time factors, lack of budget, and teacher attitudes. The factors hindering students' learning achievement were family background, lack of focus on education, and teachers' resistance to change. The roles of principals to curb these issues were collecting data on students' learning achievement, equipping teachers with knowledge and resources, being good role models, and building relationships with parents. This study highlighted that school principal 1 has shown unique ideas and approaches in improving students' learning achievement compared to school principal 2. The study suggests using descriptive analysis using more than one group of participants.</p>

How is the halal certification policy implemented? Perspective analysis of small and medium enterprises (SMEs) in Indonesia

Purpose This study aims to explore small and medium enterprises (SMEs) acceptance of the halal certification policy in Indonesia, aiming to understand their perspectives and characteristics, as well as the primary considerations of business actors in implementing the policy. This study seeks to provide a comprehensive understanding of SME actors’ views toward halal certification policies, which is crucial for strengthening the government’s efforts in building a robust halal system and creating awareness in the community. Design/methodology/approach This study uses a mixed method. This study uses a random sampling technique on SMEs in Bandung, Indonesia. A total of 400 respondents participated in filling out the study questionnaire. Meanwhile, five SME actors were interviewed to gain deeper insight into the topic of this study. The data analysis technique used descriptive analysis and verification with confirmatory factor analysis. Findings The results of the study indicate that the halal certification policy is generally accepted by business actors, but there are criticisms regarding knowledge and information about halal certification. Halal awareness and perceived effectivity have the highest acceptance scores, while halal knowledge and information, religious behavior, individual background, and personal and social aims have the lowest scores. All acceptance indicators meet the criteria of a good fit model, with system indicators having a greater impact. Acceptance is based not only on theological–religious considerations but also on pragmatic considerations related to business operations. Research limitations/implications This study has several limitations that should be considered. First, the topics and variables studied are focused only on the dimensions of acceptance of the halal certification policy. It would be more comprehensive if integrated with other variables in correlational and implicative studies. Second, the measurement model used in this study is modified from the policy acceptance model, which focuses on normative and systemic aspects of the policy without considering theological values of the halal certification policy. A more complex model is required to measure the acceptance of a comprehensive halal certification policy that considers both normative and theological aspects. Practical implications The implications of this study are as follows: First, the implementation of the halal certification policy must take into account the various indicators of policy acceptance, particularly from the business actors who are responsible for implementing the policy. Second, the implementation of the halal certification policy must also take into account the heterogeneous characteristics of the business actors. Third, the certification policy should focus on two critical indicators, namely, halal awareness and the perceived effectivity of policy implementation, which can be reinforced by other indicators. Social implications The results of this study confirm that the government must take into account the response of business actors to ensure the effectiveness of implementing the halal certification policy. The government can take an important step in this regard by conducting a survey of business actors who have participated in the halal certification program to understand the benefits and satisfaction they receive from the policy and identify the factors that hinder them from accepting the halal certification policy. Originality/value This study highlights the response of SME actors regarding the acceptance of the halal certification policy. This study provides a new perspective regarding the acceptance of SMEs toward halal certification policies that are important for future implementation.

Development of a Pilot Literacy Scale to Assess Knowledge, Attitudes, and Behaviors towards Climate Change and Infectious Disease Dynamics in Suriname.

Prior research has shown that climate literacy is sparse among low- and middle-income countries. Additionally, no standardized questionnaire exists for researchers to measure climate literacy among general populations, particularly with regards to climate change effects on vector-borne diseases (VBDs). We developed a comprehensive literacy scale to assess current knowledge, attitudes, and behaviors towards climate change and VBD dynamics among women enrolled in the Caribbean Consortium for Research in Environmental and Occupational Health (CCREOH) cohort in Suriname. Items were generated by our research team and reviewed by a group of six external climate and health experts. After the expert review, a total of 31 climate change and 21 infectious disease items were retained. We estimated our sample size at a 10:1 ratio of participants to items for each scale. In total, 301 women were surveyed. We validated our scales through exploratory (n = 180) and confirmatory factor analyses (n = 121). An exploratory factor analysis for our general Climate Change Scale provided a four-construct solution of 11 items. Our chi-squared value (X2 = 74.32; p = 0.136) indicated that four factors were sufficient. A confirmatory factor analysis reinforced our findings, providing a good model fit (X2 = 39.03; p = 0.23; RMSEA = 0.015). Our Infectious Disease Scale gave a four-construct solution of nine items (X2 = 153.86; p = 0.094). A confirmatory factor analysis confirmed these results, with a chi-squared value of 19.16 (p = 0.575) and an RMSEA of 0.00. This research is vitally important for furthering climate and health education, especially with increases in VBDs spread by Aedes mosquitoes in the Caribbean, South America, and parts of the southern United States.

Modelling Polyphenol Extraction through Ultrasound-Assisted Extraction by Machine Learning in Olea europaea Leaves.

The study of the phenolic compounds present in olive leaves (Olea europaea) is of great interest due to their health benefits. In this research, different machine learning algorithms such as RF, SVM, and ANN, with temperature, time, and volume as input variables, were developed to model the extract yield and the total phenolic content (TPC) from experimental data reported in the literature. In terms of extract yield, the neural network-based ANNZ-L model presents the lowest root mean square error (RMSE) value in the validation phase (9.44 mg/g DL), which corresponds with a mean absolute percentage error (MAPE) of 3.7%. On the other hand, the best model to determine the TPC value was the neural network-based model ANNR, with an RMSE of 0.89 mg GAE/g DL in the validation phase (MAPE of 2.9%). Both models obtain, for the test phase, MAPE values of 4.9 and 3.5%, respectively. This affirms that ANN models would be good modelling tools to determine the extract yield and TPC value of the ultrasound-assisted extraction (UAE) process of olive leaves under different temperatures, times, and solvents.

In Vitro Model of Prepacked Carbon Dioxide Absorber Use: Development and Testing.

Carbon dioxide absorbers allow the use of fresh gas flow below minute ventilation (V˙E). Models are developed and tested in vitro to quantify their performance with variable carbon dioxide load (V˙CO2), fresh gas flow, V˙E, end-tidal carbon dioxide (ETco2) fraction, and the type of workstation used. First principles are used to derive a linear relationship between fresh gas flow and fractional canister usage or FCU0.5 (the reciprocal of the time for the inspiratory carbon dioxide fraction to reach 0.5%). This forms the basis for two basic models in which V˙E was measured by spirometry or calculated. These models were extended by multiplying V˙E with an empirical workstation factor. To validate the four models, two hypotheses were tested. To test whether the FCU0.5 intercept varied proportionally with V˙CO2 and was independent of V˙E, FCU was measured for 10 canisters tested with a fixed 0.3 l/min fresh gas flow and a range of V˙CO2 while V˙E was either constant or adjusted to maintain ETco2 fraction. A t test was used to compare the two groups. To confirm whether a change in V˙CO2 accompanied by a change in V˙E to maintain ETco2 fraction would shift the linear fresh gas flow-FCU0.5 relationship in a parallel manner, 19 canisters were tested with different combinations of V˙CO2 and fresh gas flow. These measured FCU values were compared to those predicted by the four models using Varvel's performance criteria. With 0.3 l/min fresh gas flow, FCU0.5 was proportional with V˙CO2 and independent of whether V˙E was adjusted to maintain ETco2 fraction or not (P = 0.962). The hypothesized parallel shift of the fresh gas flow-FCU0.5 relationship was confirmed. Both extended models are good candidate models. The models predict prepacked canister performance in vitro over the range of V˙E, fresh gas flow, and V˙CO2 likely to be encountered in routine clinical practice. In vivo validation is still needed.

Assessing the Impacts of Climate Change on the At-Risk Species Anaxyrus microscaphus (The Arizona Toad): A Local and Range-Wide Habitat Suitability Analysis

Anaxyrus microscaphus (The Arizona Toad) is an at-risk species that is endemic to the southwestern United States. Despite conservation concerns, little is known about the ecological drivers of its distribution and habitat use. We investigated the potential distribution of A. microscaphus at the range-wide scale and local scales (i.e., Zion National Park), using MaxEnt to model habitat suitability under current and future climate scenarios. Our models incorporated 12 environmental variables, including climatic, geomorphological, and remotely sensed data. The results showed good model accuracy, with temperature and elevation being the top contributing variables. Currently, 42.6% of the park’s area provides a suitable habitat for A. microscaphus, but projections for 2050 and 2070 indicate a significant reduction in suitable habitat across its range. Temperature was the most influential variable, with habitat suitability decreasing as the annual mean temperatures exceeded 10 °C. Precipitation, vegetation, and topography variables also significantly contributed to the models. The most suitable habitat within Zion National Park occurred along sloped rivers and streams and in valleys with sandy soils, emphasizing the importance of riparian habitat conservation for A. microscaphus survival and persistence. As climate change progresses, the species’ habitat is expected to become increasingly constrained across local and range-wide scales. Our models demonstrated a shift in the suitable habitat towards major river systems, indicating a potential reliance on larger permanent river systems as smaller, more ephemeral habitats decrease in size and abundance. Future management strategies should prioritize conserving and enhancing the resilience of these habitats. MaxEnt models can guide population survey efforts and facilitate the identification of priority conservation areas, saving time and resources for species of concern such as A. microscaphus. Further research, including field surveys and large-scale analyses, is necessary to further refine our understanding of this species’ distribution and how it may be impacted by climate and habitat change.

Whole-genome Sequencing Reveals Autooctoploidy in Chinese Sturgeon and Its Evolutionary Trajectories.

The order Acipenseriformes, which includes sturgeons and paddlefishes, represents "living fossils" with complex genomes that are good models for understanding whole-genome duplication (WGD) and ploidy evolution in fishes. Here, we sequenced and assembled the first high-quality chromosome-level genome for the complex octoploid Acipenser sinensis (Chinese sturgeon), a critically endangered species that also represents a poorly understood ploidy group in Acipenseriformes. Our results show that A. sinensis is a complex autooctoploid species containing four kinds of octovalents (8n), a hexavalent (6n), two tetravalents (4n), and a divalent (2n). An analysis taking into account delayed rediploidization reveals that the octoploid genome composition of Chinese sturgeon results from two rounds of homologous WGDs, and further provides insights into the timing of its ploidy evolution. This study provides the first octoploid genome resource of Acipenseriformes for understanding ploidy compositions and evolutionary trajectories of polyploid fishes.

A Phenomapping Tool and Clinical Score to Identify Low Diuretic Efficiency in Acute Decompensated Heart Failure

BackgroundIndividuals with acute decompensated heart failure (ADHF) have a varying response to diuretic therapy. Strategies for the early identification of low diuretic efficiency to inform decongestion therapies are lacking. ObjectivesThe authors sought to develop and externally validate a machine learning–based phenomapping approach and integer-based diuresis score to identify patients with low diuretic efficiency. MethodsParticipants with ADHF from ROSE-AHF, CARRESS-HF, and ATHENA-HF were pooled in the derivation cohort (n = 794). Multivariable finite-mixture model-based phenomapping was performed to identify phenogroups based on diuretic efficiency (urine output over the first 72 hours per total intravenous furosemide equivalent loop diuretic dose). Phenogroups were externally validated in other pooled ADHF trials (DOSE/ESCAPE). An integer-based diuresis score (BAN-ADHF score: blood urea nitrogen, creatinine, natriuretic peptide levels, atrial fibrillation, diastolic blood pressure, hypertension and home diuretic, and heart failure hospitalization) was developed and validated based on predictors of the diuretic efficiency phenogroups to estimate the probability of low diuretic efficiency using the pooled ADHF trials described earlier. The associations of the BAN-ADHF score with markers and symptoms of congestion, length of stay, in-hospital mortality, and global well-being were assessed using adjusted regression models. ResultsClustering identified 3 phenogroups based on diuretic efficiency: phenogroup 1 (n = 370; 47%) had lower diuretic efficiency (median: 13.1 mL/mg; Q1-Q3: 7.7-19.4 mL/mg) than phenogroups 2 (n = 290; 37%) and 3 (n = 134; 17%) (median: 17.8 mL/mg; Q1-Q3: 10.8-26.1 mL/mg and median: 35.3 mL/mg; Q1-Q3: 17.5-49.0 mL/mg, respectively) (P < 0.001). The median urine output difference in response to 80 mg intravenous twice-daily furosemide between the lowest and highest diuretic efficiency group (phenogroup 1 vs 3) was 3,520 mL/d. The BAN-ADHF score demonstrated good model performance for predicting the lowest diuretic efficiency phenogroup membership (C-index: 0.92 in DOSE/ESCAPE validation cohort) that was superior to measures of kidney function (creatinine or blood urea nitrogen), natriuretic peptide levels, or home diuretic dose (DeLong P < 0.001 for all). Net urine output in response to 80 mg intravenous twice-daily furosemide among patients with a low vs high (5 vs 20) BAN-ADHF score was 2,650 vs 660 mL per 24 hours, respectively. Participants with higher BAN-ADHF scores had significantly lower global well-being, higher natriuretic peptide levels on discharge, a longer in-hospital stay, and a higher risk of in-hospital mortality in both derivation and validation cohorts. ConclusionsThe authors developed and validated a phenomapping strategy and diuresis score for individuals with ADHF and differential response to diuretic therapy, which was associated with length of stay and mortality.

Development and validation of a nomogram model for predicting the risk of venous thromboembolism in lymphoma patients undergoing chemotherapy: a prospective cohort study conducted in China

Background The mechanism of Venous thromboembolism (VTE) is complicated and difficult to prevent due to factors such as bone marrow invasion, therapy, and immune-mediated effects. This study aims to establish a nomogram model for predicting the risk of thrombosis in lymphoma patients undergoing chemotherapy, which has been increasing over the past 30 years. Methods The data of lymphoma patients from the Affiliated Cancer Hospital of Chongqing University in China between 2018 and 2020 were analyzed. This included age, sex, body mass index, ECOG score, histological type, Ann Arbour Stage, white blood cells count, haemoglobin level, platelet count, D-dimer level, and chemotherapy cycle. Univariate and multivariate cox analysis was used to determine the risk factors for VTE. Characteristic variables were selected to construct a nomogram model which was then evaluated using ROC curve and calibration. Results Age, sex, PLT, D-dimer and chemotherapy cycle were considered as independent influencing factors of VTE. The mean (standard deviation) of the C index, AUC and Royston D statistics of 1000 cross-validations of the Nomogram model were 0.78 (0.01), 0.81 (0.01) and 1.61(0.07), respectively. It indicates a good calibration degree and applicability value as shown by the calibration curve. The DCA curve showed a rough threshold range of 0.05–0.60 with a good model. Conclusions We have established and validated a nomogram model for predicting the risk of thrombosis in lymphoma patients. This model can assess the risk of thrombosis in each individual patient, enabling the identification of high-risk groups and targeted preventive treatment.

Validating a scale to measure self-regulated learning strategies for independent listening beyond the EFL classroom

The present study aimed to validate a self-report questionnaire created and used in Yabukoshi (2023) to assess learners’ perceived use of self-regulated learning (SRL) strategies for practicing listening skills to improve the TOEIC® listening scores outside the classroom in an English as a foreign language (EFL) context. The instrument comprised 14 items on metacognitive SRL strategies used for out-of-class listening practice, which were divided into three subscales: strategies used in the forethought, performance, and self-reflection phases, drawing on Zimmerman's SRL model. The questionnaire was administered to 135 EFL undergraduates in Japan and subjected to a psychometric evaluation to determine its structural aspect of validity through reliability tests and confirmatory factor analysis (CFA), as well as to assess its convergent and discriminant validity and its external aspect of validity (i.e., predictive validity). The instrument had sufficient internal consistency based on reliability tests (Cronbach's alpha). The CFA results indicated a relatively good and reasonable model fit, and the convergent validity was found to be adequate. The discriminant validity was not satisfactory, which was discussed based on SRL theory and previous empirical evidence. Multiple regression analysis revealed that the three strategy factors as a whole were a strong predictor of learners’ listening proficiency. The empirical evidence provides preliminary support for the application of SRL theory to the field of EFL listening. The results of this study contribute to the limited research on the assessment of SRL strategy use for listening practice outside EFL classrooms.

Iopamidol Abatement from Waters: A Rigorous Approach to Determine Physicochemical Parameters Needed to Scale Up from Batch to Continuous Operation.

The abatement of iopamidol (IPM), an X-ray iodinated contrast agent, in aqueous solution using powdered activated carbon (PAC) as a sorbent was investigated in the present work. The material was characterized by various analytical techniques such as thermogravimetric analysis, scanning electron microscopy, transmission electron microscopy, Brunauer-Emmett-Teller analysis, dynamic light scattering, and zeta potential measurements. Both thermodynamic and kinetic experiments were conducted in a batch apparatus, and the effects of the initial concentration of IPM, the temperature, and the adsorbent bulk density on the adsorption kinetics were investigated. The adsorption isotherms were interpreted well using the Langmuir model. Moreover, it was demonstrated that IPM adsorption on PAC is spontaneous and exothermic (ΔH0 = -27 kJ mol-1). The adsorption kinetic data were described using a dynamic intraparticle model for fluid-solid adsorption kinetics (ADIM) allowing determination of a surface activation energy Es = 6 ± 1 kJ mol-1. Comparing the experimental results and the model predictions, a good model fit was obtained.

Teachers' and Principals' Efforts in Implementing Character Education for Elementary School Students

The efforts of teachers and principals are very important in student character education because the teachers are role models for all students and the principal as management who is able to organize the smooth learning and teaching process. This research uses qualitative methods and descriptive approaches with observation, interview, and documentation tools. The data analysis used using the Miles and Huberman model includes data collection, data reduction, data display, verification, or drawing. The results showed that teachers strive to implement character in students by giving instruction or advice that builds the student's character, developing strategies to implement character building in students, providing good role models for students, approaches to understanding of the student character and innovative approaches use learning methods and media and integrated character development. While principals strive to provide extracurricular and noncurricular programs for students integrated with character education, provide subjects integrated with character education, provide facilities and infrastructure to support character education, direct teachers to provide role models for students, with the community work or parents of students to support the character development of the students.

Mathematical Modeling of Gait for Lower Limb Exoskeleton

This study presents the mathematical Modeling of gait. This model is for the lower limb exoskeleton. The exoskeleton has wide scope in hospitals, physical training, and army. The comfortable gait with exoskeleton requires a good mathematical model of gait. This Modeling of this study starts with a C3D file which is taken from a hospital. This Modeling uses MLS viewer, MOKKA, Any Body, and Matlab software. The basic information of the C3D file read with the MLS viewer software. This software tells the type of force plate, name of maker points, the number of force plate and marker points use in the gait analysis. The motion of marker points visualizes in MOKKA software. These visuals in MOKKA software give the position of all marker points. The MOKKA software also gives information about the starting frame number and last frame number for the gait on the force plates. The information collected from the MLS viewer and MOKKA software uses for modification of Any Script of the inbuilt model of Any Body software. The kinematic and inverse dynamic analysis of C3D file data performs in Any Body software after proper changes in Any Script of the model. The linear position and velocity data obtained from kinematic analysis use in Mat lab Modeling. Mat lab Modeling has two-step: curve fitting and curve plotting. The sum of sine equation fits on this linear position and velocity data using the curve fitting app of Mat lab. Another velocity equation is evaluated by the differentiation of the position equation. These equations of linear position and velocity simulate using Mat lab software. The plot of kinematic analysis data and plot of modeled equations compare in the Mat lab software. The goodness of the results of all these equations is decided based on root mean square error (RMSE). Keywords: Gait Analysis; Biomechanics; C3D files; Anybody Software; Root mean square error (RMSE); Electromyography(EMG); Open Sim; Mokka Analysis; Any Body Analysis; MLS viewer; Mat Lab Modeling.

The cilium like region of the Drosophila bifurca spermatocyte: Elongation of a giant axoneme without intraflagellar transport

AbstractThe growth of the ciliary axonemes mainly depends on the evolutionary conserved intraflagellar transport (IFT) machinery. However, insect spermatocytes are characterized by cilium‐like regions (CLRs) that elongate in the absence of IFT. It is generally believed that the dynamics of these structures relies on the free diffusion of soluble tubulin from the cytoplasm. However, this passive process could allow the elongation of short ciliary axonemes, but it is unclear whether simple diffusion of tubulin molecules can ensure the correct assembly of elongated ciliary structures. To decipher this point we analyzed the assembly of the CLRs held by the primary spermatocytes of Drosophila bifurca. These ciliary structures consist of a very elongated axoneme that grows without IFT and, therefore, could represent a good model in which to evaluate the role played by the free diffusion of soluble tubulin. The observation of wavy microtubules in the axonemal lumen of fully elongated CLRs of D. bifurca may be consistent with the diffusion of tubulin within the axonemal lumen. Progressive consumption of soluble tubulin used for axoneme growth at the apical tip of the CLRs could result in a gradient sufficient to move tubulin from the cytoplasm to the apical end of the forming ciliary structure. When the axoneme reaches its full length, tubulin molecules are not drawn to the tip of the CLRs and accumulate at the base of the axoneme, where its concentration may exceed the threshold need for microtubule polymerization. The presence of γ‐TuRCs at the proximal ends of the supernumerary microtubules could enhance their nucleation.