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One of the points of concern in public administration is the organising of democratic public services. Democratic public service is the basic essence in realizing justice and social welfare. This can be realized if it involves all state stakeholders and domains in the administration of the government. In this perspective, public services should obtain genuine attention, be processed professionally and properly provided to residents of service users. Billboard licence is one of the types of licensing services issued by the government along with the rapid growth of companies or industries that have an impact on the increase in regional revenue. In addition to increasing regional revenue, the increase in billboards is directly proportional to various violations that occur because of services provided so that they are important to be handled. The purpose of this study is to evaluate the degree to which the Regional Revenue Agency of Makassar City, one of the government organisers in public services, organises democratic public services, particularly in the execution of billboards. The study employs a qualitative method and includes both primary and secondary data. Through in-depth interviews and observation, primary data is gathered. secondary information obtained from documents. Data reduction is then used to process the acquired data. The results of the study show that democratic public services have not been implemented. Complexity, bureaucracy, apparatus performance and community attitudes towards public services are factors that influence service integrity.

Background: Human dental pulp stem cells (HDPSCs) may be differentiated into neural lineages. The main aim of the study was to assess the DNA demethylation and histone deacetylation inhibition on the differentiation of HDPSCs into neural progenitor-like cells (NPCs). Methods: HDPSCs were treated with 5-aza2′-deoxycytidine (AZA), DNA methylation inhibitor, and the histone deacetylase inhibitor suberoylanilide hydroxamic acid (SAHA) for 3 and 5 days followed by their differentiation into NPCs. The efficiency of the differentiation was evaluated by apoptosis, cellular proliferation, and relative expression of Nestin among the NPCs derived with the different treatments. Results: Five-day treatment of AZA was crucial for the more efficient demethylation of the HDPSCs. Analysis of the proliferation, apoptosis, and relative expression of the Nestin indicated that the AZA and SAHA neither enhance nor inhibit the differentiation of the HDPSCs into NPCs. Howevere, the expression of Nestin decreased at day 7 in NPCs derived with SAHAH treatment compared with NPCs derived with AZA treatmement. However, there was no difference in Nestin expression in any treatment-derived NPCs compared with control NPCs. All of the NPCs derived from all of the groups were able to differentiate into terminal neurons. Conclusion: Neither DNA demethylation nor the histone deacetylation has any main effects on proliferation and apoptosis during the differentiation of HDPSCs into NPCs. The only significant effect of the treatments was on the size of the NPCs at day 7; the SAHAH treatment had the smallest NPCs.

This work presents a novel and highly compact broadband Yagi antenna structure in multilayer configuration for Ku band applications. The antenna is formed by stacking two identical Yagi elements which are fed in-phase with a single strip-based transmission line. Metalized vias has been used to connect the ground planes and to launch the signal in the driver element of both Yagi elements. The design has multiple advantages of providing large gain, large impedance bandwidth, high front-to-back ratio along with low radiation leakage. The unique broadside coupling introduced in this topology causes constructive interference of near fields in the H-plane thus causing wider HPBW. Detailed optimization processes along with physical insight have been provided for a better understanding of the working principle. The design has been extended into a $1 \times 4$ antenna array formation in the E-plane to enhance the boresight gain. The array thus formed offers a fractional bandwidth of 26.6% over the frequency range from 16.51 GHz to 21 GHz. It produces a gain of 11.83 dBi with a front-to-back ratio of 33.2 dB. The HPBW in the H-plane is measured to be 94.7° which allows this antenna system to be used in cellular communication, scanning, and surveillance system.

The way students who want to become teachers represent their mathematical reasoning when they solve mathematical problems—using case studies and qualitative techniques. Data were gathered from the vignette results of student work. They are using snowball sampling for subject selection. Three third-semester mathematics education program participants served as the study's research subjects—ways for gathering data, such as interviewing and recording. Three steps of the analysis were completed: presentation of data, elaboration of conclusions and verification. As a consequence of meeting all markers of mathematical thinking representation, the S1 and S2 subjects with high and moderate academic talents had good mathematical thinking representation abilities. Because S3 students with limited intellectual skills cannot still represent mathematical ideas.

It has been observed that income inequality is an economic element that may impede a nation's economic development. In general, Indonesia's Gini ratio has remained low for nearly a decade, although one region, Yogyakarta Province, unexpectedly exceeds the national average. The provincial government of Yogyakarta must focus more on reducing income inequality. Therefore, this study employs the Poverty-Growth-Inequality Triangle model approach to investigate the complexity of income inequality in Yogyakarta Province. The data is collected from five cities in Yogyakarta Province from 2010 to 2021. For the quantitative study, a Simultaneous Equation Model analysis with three iterations of least squares is performed. The results indicate that there is no causal relationship between income inequality and economic growth or poverty. According to the model of income inequality, education and the district minimum wage have a significant impact on income inequality. Therefore, local governments are advocated to evaluate policies aimed at reducing income inequality through education system reform, equity in district minimum wage and economic growth, and efficiency in the utilization of income inequality-related funds.

Free space optical (FSO) communication offers huge bandwidth, license-free spectrum and a more secure channel. PIN diodes are normally used for detection, but avalanche photodiodes (APD) are preferred for detecting high-speed FSO signals in many applications. In the case of APD, the noise distribution is input-dependent Gaussian noise (IDGN) rather than input-independent Gaussian noise (IIGN). We investigate the error analysis using on-off keying (OOK) for various detection approaches. This paper proposes a machine learning approach and compares its performance with soft and hard decisions. Soft values in the case of IDGN and IIGN are derived, and the optimum and sub-optimum detection thresholds are evaluated. The proposed novel ML approach shows better performance gains than the other approaches. It is also demonstrated that the IDGN model should have an optimum detection and achieve a gain of 2.5[dB] and about 1[dB] at $\lambda $ = 0[dB] and $\lambda $ = 10[dB], respectively. Experimental results are plotted for the FSO channel data, and a model fit curve is plotted using the ML approach.

Penelitian ini berujuan Untuk mengetahui sumber pemahaman hadis Nabi yang diimplementasikan oleh umat Islam dalam kehidupannya, serta menganalisa akar pemahaman dari ormas Islam yang ada di Majene dalam memahami hadis-hadis Nabi saw. sehingga jelas afiliasinya. Penelitian ini menggunakan jenis penelitian kualitatif dengan metode analisis konten. pendekatan yang digunakan yaitu pendekatan historis, dan pendekatan Sosial yang difokuskan pada tiga ormas Islam yaitu Muhammadiyah, Nahdatul Ulama dan Darud Dakwah wal Irsyad yang bertempat di Majene. Hasil penelitian ini ditemukan bahwa ormas Muhammadiyah sangat selektif menggunakan hadis sebagai hujjah dengan penekanan pada hadis yang shaẖih sekalipuh dalam masalah fadlâilul ‘amal. Pernyataan ini tertuang dalam Putusan Majelis Tarjih bahwa Hadis mauqûf tidak dapat dijadikan hujjah kecuali status hukumnya marfû’. Pengikut Muhammadiyah di Majene dalam praktek keagamaannya ada dua model yaitu Muhammadiyah puritan dan Muhammadiyah adaptif. Adapun ormas NU mendefinisikan hadis sejalan dengan empat imam madzhab dan jumhur ulama ahli hadis. Adapun ke-hujjah-an hadis dhâ’if dalam penetapan hukum tasyri’, maka para ulama tidak memperbolehkan. Hadis dhâ’if bisa digunakan dalam hal fadhailul ‘âmal (keutamaan beramal), bukan sebagai argumen hukum dan aqidah, itupun dengan beberapa syarat yang harus terpenuhi, sedangkan Ormas DDI dalam pemikiran keagamaan dan pengamalan ajaran agama Islam, hampir sama dengan apa yang dilakukan oleh NU, baik dari aspek pemahaman teologi, fikih, tasawuf dan pengkajian hadis. Khusus dalam kajian hadis, ormas DDI mengikut pada jumhur ulama hadis dalam aspek pemaknaan hadis. Apabila hadis itu kualitasnya shahih ataupun hasan, maka hadis tersebut dapat di amalkan. Demikian pula hadis dhaif bisa diamalkan jika terkait dengan fadhail al-amal

This study aims to determine the types of errors students face when solving math problems. First, review the error types based on Watson's criteria and student learning styles. This study uses an explanatory sequential design model. Data analysis techniques include Quantitative data analysis techniques, descriptive statistics, and inferential statistics. At the same time, the qualitative data analysis techniques include; data reduction, data presentation, and conclusion. The results showed that the errors based on Watson's criteria and learning styles obtained were based on student responses, including; Inappropriate Data 40%, Omitted Conclusion 20%, Response Level Conflict 40%, and Above Other 40%. Furthermore, the types of errors obtained in classroom learning include Inappropriate Data 25%, Omitted Conclusion 50%, and Skill Hierarchy Problems 25%. In the visual learning pattern, there are five error classes: Inappropriate Data 9%, Omitted Conclusion 55%, Response Level Conflict 18%, Skill Hierarchy Problem 27%, and Above Other 18%. Several factors influence the error, including; the decline in students' motivation, interest, and thinking skills. Efforts can be made to minimize student errors, including increasing practice on story questions and eliminating students' negative mindset towards learning mathematics

The OKI District Population and Civil Registration Service have implemented the employee attendance information system by utilizing a fingerprint machine. This system is quite helpful in recording employee attendance properly. However, several obstacles are found in the implementation of the system. Namely, calculating the attendance percentage is still done manually because the data must be further processed using additional applications. Based on these obstacles, this study aims to implement web service technology using the protocol SOAP to integrate the system currently used. The system will automatically download fingerprint machine data and process it into attendance percentage reports, so that it can be more optimal and increase efficiency. The data obtained will be used by the staffing department, including one of the factors for measuring employee performance and determining Additional Employee Income (TPP).

The current research was conducted to investigate and compare the role of functional foods such as probiotics and prebiotics alone or in combinations on the markers of liver damage, oxidative stress markers and inflammatory markers in the nonalcoholic fatty liver disease (NAFLD) induced rats. According to the results, G3, G4 and G6 gained significant weight at the end of the study. Moreover, the weights of different organs (liver, Spleen and kidney) revealed that G1 (control negative) fed on a standard diet gained the lowest liver weight, G2 (control positive) fed on high fat diet (HFD) gained maximum weight (9.63 ± 0.46 g). In addition, the symbiotic group (G8) lowered the liver organ weight (6.77 ± 0.20 g), indicating that HFD induced fat deposition in body and other body organs. Furthermore, results of serum liver function markers were concerned, Maximum reduction of Alanine aminotransferase (ALT) was found among the G8 (Probiotics, GOS and Inulin) and G4 (GOS). Aspartate aminotransferase (AST) was significantly reduced among all the treatments compared to the control positive. Alkaline phosphate (ALP) was reduced among G5, G6 and G7. Gamma-glutamyl transferase (GGT) remained unaffected during the trial. As far as the results of tumor necrotic factor (TNF) were concerned, probiotics and GOS groups had a significant reduction in the levels of TNF after 19 weeks of study. Upon the prebiotics and probiotics therapy, a strong association was found with the hepatic inflammation at various degrees and hepatic and portal inflammation was reduced among the symbiotic groups significantly (Chi-square value = 49.04**; P-value = 0.000; ** = Highly significant (P

Keeping in view the latest development of anti-Hermitian matrix in mind, we construct some closed form formula for a classical system of matrix equations having anti-Hermitian nature in this paper. We give the necessary and sufficient conditions for the existence of its solution by applying the properties of matrix rank. The general solution to this system is expressed by closed formula based on generalized inverses of given matrices. The novelty of the proposed results is not only obtaining a formal representation of the solution in terms of generalized inverses but the construction of an algorithm to find its explicit expression as well. To conduct an algorithm and numerical example, it is used the determinantal representations of the Moore Penrose inverse previously obtained by one of the authors.

Background: Hermetia illucens L. have gained popularity in recent years as an environmentally friendly response to both the present and potential future food/feed crisis. The larvae of H. illucens L., or black soldier fly larvae (BSFL), is an alternative solution to tackle the issue of organic waste bioconversion. However, understanding the environmental loads associated with biowaste bioconversion using BSFL to produce dried BSFL is a pivotal point to keep the environment sustainable. This study reported a life cycle assessment (LCA) of the biowaste bioconversion process of BSFL and determined the environment impact analysis to make recommendations for modifications to lessen environmental consequences. Methods: The methodology used is life cycle assessment (LCA), which includes: (a) system boundary determination (gate-to-gate), starting from biowaste production, biowaste bioconversion, prepupae and BSFL frass production. The system boundary of the dried BSFL production is designed for both the processing and production of one cycle of BSFL; (b) life cycle inventory activities carried out at PT Biomagg Sinergi Internasional, Depok, West Java, Indonesia; (c) conducting life cycle impact assessment on five environmental impact categories namely global warming potential (GWP), acidification (AC), terrestrial eutrophication (TE), fossil fuel depletion (FFE), eco-toxicity (ET); and (d) interpretation of the assessment result. The LCA is conducted using openLCA 1.11 software and TRACI 2.1 impact assessment method. Results: The impact values of GWP, AC, TE, FFE, and ET, per 100 kg of BSFL dried production was 6.687 kg CO 2 eq; 0.029 kg SO 2-eq; 0.092 kg N-eq; 16.732 MJ surplus; 121.231 CTUe. Production of prepupa had the highest hotspots in these emissions, followed dried BSFL production. Conclusions: Efforts to reduce environmental impacts that can be done are by implementing an integrated rearing system using substrate from a single type of known substrate for BSFL and using alternative drying methods for BSFL dried production.

Local Government Administration Arrangement Is part of Political Development in Aoma Village, Wolasi District, South Konawe Regency, The purpose of the study is to find out the arrangement of government administration in supporting the service This location selection is based on the consideration that the implementation of government administrative services needs to be arranged optimally for service improvement. Used qualitative descriptive research where data collection is carried out in natural conditions (natural setting), primary data sources and data collection techniques are more in-depth interviews and documentation. Data analysis of categorization, reduction, and interpretation. The results of the study showed the arrangement of the implementation of government administration in Aoma Village, Wolasi District, South Konawe Regency in the form of government by providing services to the community in the form of population administration activities, carrying out data collection and inventory of village assets.

Objective: To assess the accuracy of portal vein pulsatility (VPI) for non-invasive diagnosis of high-risk non-alcoholic fatty liver disease (NAFLD). Study Design: Cross-sectional study. Place and Duration of Study: Pakistan Institute of Medical Science, Islamabad Pakistan, from Jan to May 2022. Methodology: Duplex Doppler ultrasound was used to examine the main portal vein in patients with a biopsy-proven Nonalcoholic fatty liver disease (NAFLD) diagnosis. Patients were evaluated by Doppler ultrasonography after fasting for four hours in accordance with standard methodology. The maximum (Vmax) and minimum (Vmin) blood velocities in the portal veins were measured using the spectral waveform. Results: Out of 240 NAFLD patients, 102(42.50%) were males, and 138(57.50 %) were females. According to the Non-alcoholic Steatohepatitis clinical research network (NASH CRN) scoring system, 95(39.58%) patients had F0 disease, 80(33.33%) had F1, 30(12.5%) patients F2, 24(10%) patients had F3 and 11(4.58%) had F4. 50(53.76%) patients in the low-risk group and 43(46.24%) patients in the high-risk group had diabetes. Of 102 males, 73(71.56%) had low risk, and 29(28.44%) had high risk. While out of 138 females, 79(57.24%) females had low risk, and 59(42.76%) females had a high risk of NAFLD. Venous pulsatility index, NAFLD fibrosis score, FIB-4, BARD score, and APRL had statistically significant differences (p

This study reports the bactericidal activity of mucus extracts and biochemical characterization of skin mucus from five Cyprinids, including Labeo rohita, Ctenopharyngodon Idella, Gibelion catla, Hypophthalmichthys molitrix and Cirrhinus mrigala against ten different bacteria extracted from naturally infected fish. The bactericidal activity was measured based on the zone of inhibition (ZOI) and compared against Fosfomycin. Importantly, acidic mucus extracts from five fish species exhibited higher bactericidal activity than organic and aqueous extracts. The acidic skin mucus extracts of C. idella, L. rohita, and G. catla showed higher ZOI against Staphylococcus aureus, Aeromonas hydrophila, and Pseudomonas aeruginosa. The minimum inhibitory concentration (MIC) of acidic mucus extracts from C. Idella, L. rohita, and G. catla was 16 µg/mL against A. hydrophila, P. aeruginosa, and S. aureus.Further, biochemical characterization of mucus extracts showed that protein concentration was high in the acidic mucus extracts from L. rohita, C. idella, and G. catla compared to H. molitrix and C. mirigala followed by carbohydrate and lipid content. These findings suggest that skin mucus from cyprinids could be a potent source of innovative bactericidal components for fish and human-related treatments.

Abstract Insulin signaling plays a critical role in regulating various aspects of insect biology, including development, reproduction, and the formation of wing polyphenism. This leads to differentiation among insect populations at different levels. The insulin family exhibits functional variation, resulting in diverse functional pathways. Aphis gossypii Glover, commonly known as the cotton‐melon aphid, is a highly adaptable aphid species that has evolved into multiple biotypes. To understand the genetic structure of the insulin family and its evolutionary diversification and expression patterns in A. gossypii, we conducted studies using genome annotation files and RNA‐sequencing data. Consequently, we identified 11 insulin receptor protein (IRP) genes in the genomes of the examined biotypes. Among these, eight AgosIRPs were dispersed across the X chromosome, while two were found in tandem on the A1 chromosome. Notably, AgosIRP2 exhibited alternative splicing, resulting in the formation of two isoforms. The AgosIRP genes displayed a high degree of conservation between Hap1 and Hap3, although some variations were observed between their genomes. For instance, a transposon was present in the coding regions of AgosIRP3 and AgosIRP9 in the Hap3 genome but not in the Hap1 genome. RNA‐sequencing data revealed that four AgosIRPs were expressed ubiquitously across different morphs of A. gossypii, while others showed specific expression patterns in adult gynopara and adult males. Furthermore, the expression levels of most AgosIRPs decreased upon treatment with the pesticide acetamiprid. These findings demonstrate the evolutionary diversification of AgosIRPs between the genomes of the two biotypes and provide insights into their expression profiles across different morphs, developmental stages, and biotypes. Overall, this study contributes valuable information for investigating aphid genome evolution and the functions of insulin receptor proteins.

Background: Hermetia illucens L. have gained popularity in recent years as an environmentally friendly response to both the present and potential future food/feed crisis. The larvae of H. illucens L., or black soldier fly larvae (BSFL), is an alternative solution to tackle the issue of organic waste bioconversion. However, understanding the environmental loads associated with biowaste bioconversion using BSFL to produce dried BSFL is a pivotal point to keep the environment sustainable. This study reported a life cycle assessment (LCA) of the biowaste bioconversion process of BSFL and determined the environment impact analysis to make recommendations for modifications to lessen environmental consequences. Methods: The methodology used is life cycle assessment (LCA), which includes: (a) system boundary determination (gate-to-gate), starting from biowaste production, biowaste bioconversion, prepupae and BSFL frass production. The system boundary of the dried BSFL production is designed for both the processing and production of one cycle of BSFL; (b) life cycle inventory activities carried out at PT Biomagg Sinergi Internasional, Depok, West Java, Indonesia; (c) conducting life cycle impact assessment on five environmental impact categories namely global warming potential (GWP), acidification (AC), terrestrial eutrophication (TE), fossil fuel depletion (FFE), eco-toxicity (ET); and (d) interpretation of the assessment result. The LCA is conducted using openLCA 1.11 software and TRACI 2.1 impact assessment method. Results: The impact values of GWP, AC, TE, FFE, and ET, per 100 kg of BSFL dried production was 6.687 kg CO2 eq; 0.029 kg SO2-eq; 0.092 kg N-eq; 16.732 MJ surplus; 121.231 CTUe. Production of prepupa had the highest hotspots in these emissions, followed dried BSFL production. Conclusions: Efforts to reduce environmental impacts that can be done are by implementing an integrated rearing system using substrate from a single type of known substrate for BSFL and using alternative drying methods for BSFL dried production.

This study employed a novel approach by analyzing the self-healing asphalt literature based on scientometric analysis. The most difficult components of modern study are the mapping and analysis of knowledge, co-citations, and co-occurrences. Scopus was searched to find the necessary data for the analysis, which consisted of keywords, abstracts, citations, and bibliographic information. Throughout the data assessment process, the most prolific research locations, the most often referenced articles, and the most influential authors in the field of self-healing asphalt were analyzed, along with their correlations. The need for self-repairing asphalt was also emphasized, along with the main problems of using it. The keyword analysis showed that researchers have studied self-healing asphalt for crack repair in asphalt road pavements as a sustainable maintenance method. The literature study showed that heating and encapsulating rejuvenating chemicals are two techniques of self-healing asphalt. Encapsulation uses rejuvenating capsules, whereas the heating technique uses induction heating and microwave radiation. Researchers have also developed hybrid asphalt self-healing methods as enhanced self-healing for asphalt. Academics may benefit from the quantitative assessment of regions and researchers as well as the scientific description of these areas in order to form joint initiatives and spread new ideas and approaches.

A bulk volume of waste tires, an underrated global resource, is disposed of in landfills worldwide. Extracting recycled steel fibers from these tires is an evolving trend nowadays. The outcomes of concrete having steel fibers sourced from end-of-life tires are alike industrial steel fibers. Accordingly, the attention of researchers is focused nowadays on using alternative recycled steel fibers in place of industrial steel fibers in concrete. In the current study, the review focuses on waste recycle tire steel fiber (WRTSF)-reinforced concrete applications, considering different lengths and contents for finding the research gap in this research domain. The results and methods to recycle WRTSFs in existing studies are compiled and briefed. The adoption of appropriate composition and characteristics like length, diameter, content, etc., of WRTSFs can be made by using this study to improve the mechanical properties of respective composites. Therefore, the aim of this evaluation is to encourage the application of concrete reinforced with WRTSF for different construction purposes, including but not limited to pavements, tunnel linings, bridge decks, hydraulic structures, and slope stabilization. The study seeks to provide guidance on the appropriate composition and characteristics of WRTSFs to improve the mechanical properties of the composite material.

In the construction industry, the incorporation of steel fibers in ultra-high-performance concrete (UHPC) is vital for improving its mechanical characteristics. In order to identify the essential factors of UHPC, the literature on the effect of steel fibers on UHPC is reviewed using scientometric methods in this work. The review contains complex processes like knowledge mapping, co-occurrence, and co-citation. In order to analyze the bibliographic data on the impact of steel fibers on UHPC, this study makes use of contemporary methodologies for data processing, mining, analysis, presentation, and visualization. The aim is to provide direction for further research in this area by summarizing the literature. In order to achieve this goal, data from the Scopus database, including publication sources, top authors, keywords, significant publications, and nations contributing the most to the subject, are retrieved and examined. According to the scientometric analysis, the most frequently used keyword is “steel fibers,” “Construction and Building Materials” is the most popular publication source in terms of citations and articles, and China is the top-ranking nation in the industry. Academic scholars can gain from this study’s graphical and quantitative portrayal of the contributing researchers and nations by making it easier to share concepts and form collaborative initiatives. This study also shows that steel fibers can improve the mechanical properties of UHPC but their widespread manufacturing and use are dependent on factors including the fiber content and geometry.

This research intended to increase the understanding of using modern machine intelligence techniques, including multi-expression programming (MEP) and gene expression programming (GEP), for the compressive strength (CS) prediction of rice husk ash (RHA) concrete. In addition, SHapley Additive exExplanations (SHAP) analysis was made to study the impact and interaction of raw materials on the CS of RHA concrete. A comprehensive database of 192 points with six inputs (cement, specimen age, RHA, superplasticizer, water, and fine aggregate) was used for developing prediction models. This research determined that both GEP and MEP models for the CS prediction of RHA concrete yielded reliable results, which were in close agreement with the real CS. Comparing the performance of both GEP and MEP models, it was noted that MEP, with an R2 of 0.89, outperformed the GEP model having an R2 of 0.83. Additionally, SHAP analysis indicated that specimen age was the most vital measure, followed by cement, which positively correlated with CS of RHA. The overall effect of RHA was found to be more positive, suggesting RHA utilization in the optimal range of 75–100 kg/m3 in the RHA concrete mix. The use of prediction models and SHAP analysis will help the building industry assess material properties and raw material effects faster and more economical.

In this research, test methods followed by supervised machine learning (SML) modeling were used to examine the effect of glass powder as a partial sand and cement substitute on the water absorption capability of cement mortar. This study also utilized SHapley Additive exPlanations (SHAP) analysis to determine the significance of raw materials. The dataset was derived from experiments and was used to build SML-based prediction models, including support vector machine, bagging, and AdaBoost. According to the test results, using glass powder reduced the water absorption capacity of cement mortar, and the optimum glass powder contents were noted to be 10 % as cement and 15 % as a sand substitute. Additionally, the built SML models indicated good accord with test outcomes and could be applied to calculate the water absorption of cement mortar comprising glass powder. Moreover, the AdaBoost model was found to be more accurate (R2 = 0.98) than the support vector machine (R2 = 0.95) and bagging regressor (R2 = 0.95) models in terms of R2, the difference between test and estimated findings, and the assessment of the errors.

To produce highly effective electrically conductive cementitious composites and advance non-destructive structural-health monitoring techniques, graphite-based nanomaterials (GrNs) are viable conductive fillers. A comprehensive database was created for CS and ER pertinent to GrNCC’s experimental studies from open sources. It is a challenging multi objective optimization problem (MOOP) due to the requirement of both mechanical strength and electrical resistivity for the design of Graphene nanoparticles-reinforced cementitious composites (GrNCC). The current study provides an ample data-driven approach employing machine learning (ML) techniques and a non-dominated sorting genetic algorithm (NSGA-II) to address this multi objective design optimization (MODO) problem for GrNCC. ML theories quantify how important parameters affect GrNCC’s qualities. First, using processed experimental datasets, gene expression programming (GEP) is used to develop prediction models for GrNCC’s uniaxial compressive strength (CS) and electrical resistivity (ER). The findings demonstrate its superior predictive accuracy, as evidenced by high R2 of 0.92 and 0.91 and low mean absolute error (MAE) scores of 1.57 MPa, and 60.46 kΩ.cm for CS and ER, respectively. For the MODO technique, parameter analysis was performed, which aids in identifying the parameters that need to be optimized and defining their constraints. Finally, NSGA-II is used as the foundation for the MODO technique. With the proposed prediction models as objective functions, it simultaneously optimizes the CS and ER of the GrNCC. It successfully produces a collection of Pareto solutions that make it easier to choose the right parameters for the GrNCC design. The proposed MODO technique can be efficiently applied to multiobjective design and optimization of electrical and mechanical properties of GrNCC.

Sustainable development might be promoted if waste eggshells are used in cement-based materials (CBMs) by decreasing waste disposal problems, CO2 emissions, and material costs. In this regard, experimental and machine learning (ML) strategies were used to assess the flexural strength (FS) of CBMs comprising waste eggshell powder (ESP). Initially, experimental methods were carried out to evaluate the FS of ESP-based CBMs. The acquired data was utilized to predict the FS by applying ML algorithms like a decision tree and an AdaBoost regressor. The efficacy of ML techniques was measured by comparing experimental and predicted FS and applying statistical checks and k-fold evaluations. The experiment outcomes demonstrated that the FS of CBMs was improved by the inclusion of ESP at lower replacement ratios. Additionally, based on the assessment of modeling results, the AdaBoost regressor model demonstrated a higher exactness in estimating the FS of CBMs containing ESP compared to the decision tree model. The assessment of error readings also indicated the higher precision of the AdaBoost regressor model than the decision tree. According to the feature importance analysis, the fine aggregate was the component with the lowest impact for FS, whereas cement had the prime impact. The findings showed that as opposed to using ESP as a cement replacement, using ESP as an FA replacement to keep FA in less quantity and cement in larger quantity would result in enhanced strength. The construction industry can gain from ML techniques since they allow for more time- and cost-effective approaches to assessing material attributes.

The intention of this study was to examine the use of the most prevalent industrial byproduct, silica fume, as a supplementary cementitious material (SCM). Along with the typical review, this study used the scientometric review technique to statistically examine the various features of the existing literature. A scientometric-based study can deal with the massive literature data using the applicable software tool. The bibliometric data on silica fume in concrete was gathered using the Scopus search engine between 2001 and July 2022. The top publication sources, co-occurrence of keywords, highly cited authors, and active contributing countries were all examined using scientometric analysis. Additionally, the properties of composites using silica fume as the SCM were discussed. The effect of silica fume addition on compressive, split-tensile, and flexural strength, as well as the durability and microstructure of cementitious composites, were described. It was concluded that the inclusion of silica fume as an SCM improved the material's properties while also providing environmental benefits. However, there is a limit beyond which silica fume addition showed an unfavorable effect on the performance of cementitious composites. The optimum proportion of silica fume in concrete was found to be in the range of 15–25 % by mass of cement. Moreover, literature data were utilized to develop prediction models for the strengths of cementitious composites containing silica fume, and the prediction models agreed with the actual results. These prediction models could be used to test the material strength, saving both time and cost.

Objective: To assess the role played by ultrasound in evaluating plantar fasciitis and associate the findings with Magnetic resonance imaging. Study Design: Case series. Place and Duration of Study: Department of Radiology, Pakistan Institute of Medical Sciences, Islamabad Pakistan, from Nov 2020 to Apr 2021. Methodology: All the patients underwent ultrasonography and magnetic resonance imaging scanning. The study and control Groups consisted of 38 patients. Results: Out of 38 patients, plantar fascia thickness in symptomatic feet was measured with ultrasound for both the Study and Control Groups. The Control Group had slightly thinner plantar fasciitis (1.1-2.4 mm, 1.7 ± 0.06 mm; p =0.03) compared to the Study Group (2.9-6.9 mm; 4.9±1.4 mm). In addition, this study compared other plantar fasciitis diagnostic signs on sonography with the magnetic resonance imaging findings. The diagnostic accuracy of plantar fascia pathological focal echogenicity, plantar fascia oedema, perifascial oedema, and plantar fascia rupture was 15(80.6%), 12(60.7%), 15(77.1%), and 13(68.6%) respectively. The diagnostic accuracy of ultrasonography was lower while evaluating for calcaneal spurs. Conclusion: The present study concluded that ultrasonography could be the basic initial diagnostic imaging modality to confirm clinically suspected cases of plantar fasciitis. However, magnetic resonance imaging could be the preferred diagnostic modality for suspected complex pathology and lack of clinical presentation.

Due to damage to the network of nerves that regulate the muscles and feeling in the shoulder, arm, and forearm, brachial plexus injuries (BPIs) are known to significantly reduce the function and quality of life of affected persons. According to the World Health Organization (WHO), a considerable share of global disability-adjusted life years (DALYs) is attributable to upper limb injuries, including BPIs. Telehealth can improve access concerns for patients with BPIs, particularly in lower-middle-income nations. This study used deep reinforcement learning (DRL)-assisted telepresence robots, specifically the deep deterministic policy gradient (DDPG) algorithm, to provide in-home elbow rehabilitation with elbow flexion exercises for BPI patients. The telepresence robots were used for a six-month deployment period, and DDPG drove the DRL architecture to maximize patient-centric exercises with its robotic arm. Compared to conventional rehabilitation techniques, patients demonstrated an average increase of 4.7% in force exertion and a 5.2% improvement in range of motion (ROM) with the assistance of the telepresence robot arm. According to the findings of this study, telepresence robots are a valuable and practical method for BPI patients’ at-home rehabilitation. This technology paves the way for further research and development in telerehabilitation and can be crucial in addressing broader physical rehabilitation challenges.

Among breast cancer subtypes, triple-negative breast cancer stands out as the most aggressive, with patients facing a 40% mortality rate within the initial five years. The limited treatment options and unfavourable prognosis for triple-negative patients necessitate the development of novel therapeutic strategies. Photodynamic therapy (PDT) is an alternative treatment that can effectively target triple-negative neoplastic cells such as MDA-MB-231. In this in vitro study, we conducted a comparative analysis of the PDT killing rate of unbound Rose Bengal (RB) in solution versus RB-encapsulated chitosan nanoparticles to determine the most effective approach for inducing cytotoxicity at low laser powers (90 mW, 50 mW, 25 mW and 10 mW) and RB concentrations (50 µg/mL, 25 µg/mL, 10 µg/mL and 5 µg/mL). Intracellular singlet oxygen production and cell uptake were also determined for both treatment modalities. Dark toxicity was also assessed for normal breast cells. Despite the low laser power and concentration of nanoparticles (10 mW and 5 µg/mL), MDA-MB-231 cells experienced a substantial reduction in viability (8 ± 1%) compared to those treated with RB solution (38 ± 10%). RB nanoparticles demonstrated higher singlet oxygen production and greater uptake by cancer cells than RB solutions. Moreover, RB nanoparticles display strong cytocompatibility with normal breast cells (MCF-10A). The low activation threshold may be a crucial advantage for specifically targeting malignant cells in deep tissues.

This study aimed to investigate the influence of forage supply, concentrate provision, and farmers’ characteristics on the number of cattle in the breeding village. One hundred and three farmers were selected, in interviews were carried out aiming to characterize the management practices related to forage supply, concentrate supply, and farm labour. A linear model was performed to analyze the significant variables. The result showed that the number of cattle was influenced by forage stock, farmers’ experience, and occupation. the correlation analysis showed a weak correlation between forage stock and farmer experience with the number of cattle. The clustering showed the direction effect of forage stock to the right side while the farmers’ experience to the bottom of the cluster. It concluded that the forage supply and farmers’ experience have influenced the number of cattle.