Miracle-dz/UniFAR-FTUs huggingface dataset:
PROFIT PREDICTION USING MULTIPLE LINEAR REGRESSION METHODS PYTHON PROGRAMMING LANGUAGE AT PT TRI ERDNOV REZEKI

PT. Tri Erdnov Rezeki is a national private company founded in 2016 and fully under the leadership and ownership of Indonesian entrepreneurs. PT. Tri Erdnov Rezeki is also engaged in Construction Development Planning and Repair and Maintenance of Steam Aircraft and Pressure Vessels, Supply of Technical Equipment, Industrial Work Equipment, Electrical Equipment, and Machinery, especially in the Palm Oil Plantation and Power Plant Sectors. In carrying out a project, the company does not only carry out technical design but also must carry out the economic design so that the company can determine the economic feasibility of a project. However, companies often experience cost calculation errors. Data science can be utilized to predict the value achieved in a period using previous data. Data science will analyze patterns related to data with other data to produce a reference or a formula that can be used as a value prediction in the future. So, the author will use the multiple linear regression method using the Python programming language, which functions to perform statistical analysis, namely predicting profits in a project. The analysis results in this study show that the profit variable is influenced by 99.7% by the variables material cost, labor cost, and utility cost. In comparison, other variables outside the study influence the other 0.3%. The material cost variable has the most significant influence, where the value is below 0 . 05 compared to the variable labor cost and utility cost to the profit variable. The average percentage of Python prediction errors is 0.97%, where the average percentage of Python prediction errors is smaller than the average percentage of SPSS prediction errors which is 2.04%.
Design and Spray Performance Evaluation of an Air–Ground Cooperation Stereoscopic Plant Protection System for Mango Orchards

With the aim of solving the problems of high labor intensity, low operational efficiency, and poor deposition distribution uniformity in the mango canopy associated with traditional plant protection devices, an air-ground co-operation stereoscopic plant protection system consisting of an orchard caterpillar mist sprayer and a six-rotor plant protection UAV was designed to jointly undertake plant protection operations in mango orchards. We tested the spraying performance of the system on mango trees, compared with the single-machine operation, the air–ground co-operation system could significantly increase the droplet coverage on the upperside of mango leaves in each part of the canopy (a 14.7% increase for the mist sprayer and 12.9% for the UAV). This increased the active component deposition distribution uniformity in the mango canopy but could not significantly improve the deposition and coverage of droplets on the underside of leaves compared with the mist sprayer and plant protection UAV. Due to the characteristics of the mango canopy such as large leaf length and thickness and complex leaf inclination distribution, this led to poor deposition distribution uniformity of the two spray units, and the overall CV was over 150%. The pesticide active ingredients were almost uniformly distributed in the vertical direction when the application ratios (ground implements/plant protection drones) were 8/2 and 7/3, offering a promising protocol for reduced pesticide application in mango orchards. This study presents promising data that support the innovative integration of drones into crop protection programs for large canopy crops (e.g., mango) and provides guidance for the ACSPPS system in reduction and precision application research.
ANOVA Analysis and L9 Taguchi Design for Examination of Flat Slide Burnishing of Unalloyed Structural Carbon Steel

Diamond burnishing is a finishing precision machining that is often used to improve the quality characteristics of previously machined surfaces. With its help, the surface roughness can be reduced, the surface hardness can be increased, and the tensile stresses remaining in the surface after cutting can be transformed into compressive ones, and these changes can increase the service life of the components. Diamond burnishing was typically developed for processing cylindrical surfaces and is most often used for this type of surface. In this manuscript, we present a new method with the help of sliding burnishing, which can also be used on flat surfaces. By using the clamping head of a special tool into the main spindle of the vertical milling machine and moving it along a suitable path, the flat surface can be burnished. Machining experiments were carried out with the new type of tool on general-purpose, unalloyed, structural carbon steel samples on which the flat surfaces were previously generated by face milling. The examined parameters were the burnishing force F, the feed fb, and the number of passes (NoP). The L9 Taguchi experiment design was applied for executing flat slide burnishing, and the examination was conducted by ANOVA analysis. This research contributes to the field by providing insights into optimizing the burnishing process parameters for achieving desired surface quality in milling operations.
Miniature camera lens design with a freeform surface

We present a miniature camera lens design method that uses a freeform surface based on the pedal curve to the ellipse in polynomial form. Two designs are presented and their benefits of optical performance and tolerance sensitivity are compared to designs with conventional aspheric surfaces. We also reverse a freeform design using even aspherical surfaces to show that the optimization solution of a freeform design cannot be reproduced by even aspherical surfaces.
Rice Husk—Cellulose-Based Agricultural Waste Enhances the Degradation of Synthetic Dyes Using Multiple Enzyme-Producing Extremophiles

The brightly colored synthetic dyes used in the textile industry are discharged at high concentrations—for example, various azo dyes including Methylene Blue (MB) and Methyl Orange (MO)—which is a matter of global concern, as such dyes are harmful to humans and the environment. Microbial degradation is considered an efficient alternative for overcoming the disadvantages of conventional physical and chemical dye removal methods. In this study, we investigated the potential of multiple types of the enzyme-producing extremophilic bacteria Bacillus FW2, isolated from food waste leachate, for the decolorization and bioremediation of artificial synthetic dyes. The screening of enzyme production and assaying of bacterial strain enzymes are essential for enhancing the breakdown of azo bonds in textile azo dyes. The degradation efficiencies of the water-soluble dyes MB and MO were determined at different concentrations using rice husk, which is an efficient substrate. Using the rice husks, the MO was removed completely within 20 h, and an estimated 99.8% of MB was degraded after 24 h by employing shaking at 120 rpm at 40 °C—whereas a removal efficiency of 98.9% was achieved for the combination of MB + MO. These results indicate the possibility of applying an extremophilic bacterial strain, Bacillus sp. , for large-scale dye degradation in the future.
Triose Phosphate Isomerase Structure-Based Virtual Screening and In Vitro Biological Activity of Natural Products as Leishmania mexicana Inhibitors

Cutaneous leishmaniasis (CL) is a public health problem affecting more than 98 countries worldwide. No vaccine is available to prevent the disease, and available medical treatments cause serious side effects. Additionally, treatment failure and parasite resistance have made the development of new drugs against CL necessary. In this work, a virtual screening of natural products from the BIOFACQUIM and Selleckchem databases was performed using the method of molecular docking at the triosephosphate isomerase (TIM) enzyme interface of Leishmania mexicana (L. mexicana). Finally, the in vitro leishmanicidal activity of selected compounds against two strains of L. mexicana, their cytotoxicity, and selectivity index were determined. The top ten compounds were obtained based on the docking results. Four were selected for further in silico analysis. The ADME-Tox analysis of the selected compounds predicted favorable physicochemical and toxicological properties. Among these four compounds, S-8 (IC50 = 55 µM) demonstrated a two-fold higher activity against the promastigote of both L. mexicana strains than the reference drug glucantime (IC50 = 133 µM). This finding encourages the screening of natural products as new anti-leishmania agents.
Aoba_v3 bot: a multimodal chatbot system combining rules and various response generation models

In this paper, we present a multimodal dialogue system combining a neural response generation mechanism, a reranking mechanism, and a rule-based avatar control mechanism. Our system was submitted to the open track at the Fifth Dialogue System Live Competition and won second place. Remarkably, our system received the best human evaluation performance for visual information control (i.e. speaking style of avatar) in the preliminary round. The assessment of the competition evaluators revealed that our system generates natural utterances appropriate to the conversational context and topic with an appealing speaking style. Through the analysis, we found that our devices, such as post-processing on speech recognition results and the final response selection method, are effective, but we also found room for improvement, such as speech recognition errors and challenges in the reranking module. GRAPHICAL ABSTRACT
Pharmacological and Electroceutical Targeting of the Cholinergic Anti-Inflammatory Pathway in Autoimmune Diseases

Continuous dialogue between the immune system and the brain plays a key homeostatic role in various immune responses to environmental cues. Several functions are under the control of the vagus nerve-based inflammatory reflex, a physiological mechanism through which nerve signals regulate immune functions. In the cholinergic anti-inflammatory pathway, the vagus nerve, its pivotal neurotransmitter acetylcholine, together with the corresponding receptors play a key role in modulating the immune response of mammals. Through communications of peripheral nerves with immune cells, it modulates proliferation and differentiation activities of various immune cell subsets. As a result, this pathway represents a potential target for treating autoimmune diseases characterized by overt inflammation and a decrease in vagal tone. Consistently, converging observations made in both animal models and clinical trials revealed that targeting the cholinergic anti-inflammatory pathway using pharmacologic approaches can provide beneficial effects. In parallel, bioelectronic medicine has recently emerged as an alternative approach to managing systemic inflammation. In several studies, nerve electrostimulation was reported to be clinically relevant in reducing chronic inflammation in autoimmune diseases, including rheumatoid arthritis and diabetes. In the future, these new approaches could represent a major therapeutic strategy for autoimmune and inflammatory diseases.
Maternal and Infant Histo-Blood Group Antigen (HBGA) Profiles and Their Influence on Oral Rotavirus Vaccine (RotarixTM) Immunogenicity among Infants in Zambia

Live-attenuated, oral rotavirus vaccines have significantly reduced rotavirus-associated diarrhoea morbidity and infant mortality. However, vaccine immunogenicity is diminished in low-income countries. We investigated whether maternal and infant intrinsic susceptibility to rotavirus infection via histo-blood group antigen (HBGA) profiles influenced rotavirus (ROTARIX®) vaccine-induced responses in Zambia. We studied 135 mother–infant pairs under a rotavirus vaccine clinical trial, with infants aged 6 to 12 weeks at pre-vaccination up to 12 months old. We determined maternal and infant ABO/H, Lewis, and secretor HBGA phenotypes, and infant FUT2 HBGA genotypes. Vaccine immunogenicity was measured as anti-rotavirus IgA antibody titres. Overall, 34 (31.3%) children were seroconverted at 14 weeks, and no statistically significant difference in seroconversion was observed across the various HBGA profiles in early infant life. We also observed a statistically significant difference in rotavirus-IgA titres across infant HBGA profiles at 12 months, though no statistically significant difference was observed between the study arms. There was no association between maternal HBGA profiles and infant vaccine immunogenicity. Overall, infant HBGAs were associated with RV vaccine immunogenicity at 12 months as opposed to in early infant life. Further investigation into the low efficacy of ROTARIX® and appropriate intervention is key to unlocking the full vaccine benefits for U5 children.
NELLIE: Never-Ending Linking for Linked Open Data

Knowledge graphs (KGs) that follow the Linked Data principles are created daily. However, there are no holistic models for the Linked Open Data (LOD). Building these models(i.e., engineering a pipeline system) is still a big challenge in order to make the LOD vision comes true. In this paper, we address this challenge by presenting NELLIE, a pipeline architecture to build a chain of modules, in which each of our modules addresses one data augmentation challenge. The ultimate goal of the proposed architecture is to build a single fused knowledge graph out of the LOD. NELLIE starts by crawling the available knowledge graphs in the LOD cloud. It then finds a set of matching KG pairs. NELLIE uses a two-phase linking approach for each pair (first an ontology matching phase, then an instance matching phase). Based on the ontology and instance matching, NELLIE fuses each pair of knowledge graphs into a single knowledge graph. The resulting fused KG is then an ideal data source for knowledge-driven applications such as search engines, question answering, digital assistants and drug discovery. Our evaluation shows an improved $Hit \text{@} 1$ score of the link prediction task on the resulting fused knowledge graph by NELLIE in up to 94.44% of the cases. Our evaluation also shows a runtime improvement by several orders of magnitude when comparing our two-phases linking approach with the estimated runtime of linking using a naïve approach.
Finding the acceleration and speed of a light-emitting object on an inclined plane with a smartphone light sensor

This study investigates how the acceleration and speed of a light-emitting object on an inclined plane may be determined using a smartphone’s light sensor. A light-emitting object was released from the top of an inclined plane and its illuminance values were detected by a smartphone’s light sensor during its subsequent motion down the plane. Using the illuminance and time values recorded by the smartphone, the distances between the sensor and the light-emitting object can be calculated. From these known distance and time values, the uniform acceleration and speed of the light-emitting object at any time could also be determined. A second method was also used to determine these values, i.e. the analysis of video-recordings of the light-emitting object during its motion. The values found by these two different methods were in good agreement. Thus, this experiment demonstrates that a smartphone’s light sensor can be used as a reliable instrument to determine the constant acceleration and speed of light-emitting objects.
Microbial Spoilage of Traditional Goose Sausages Produced in a Northern Region of Italy

Recently, during the ripening of goose sausage, a defect consisting of ammonia and vinegar smell was noticed. The producer of the craft facility, located in Lombardia, a Northern region of Italy, asked us to identify the cause of that defect. Therefore, this study aimed to identify the potential responsible agents for the spoilage of this lot of goose sausages. Spoilage was first detected by sensory analysis using the “needle probing” technique; however, the spoiled sausages were not marketable due to the high ammonia and vinegar smell. The added starter culture did not limit or inhibit the spoilage microorganisms, which were represented by Levilactobacillus brevis, the predominant species, and by Enterococcus faecalis and E. faecium. These microorganisms grew during ripening and produced a large amount of biogenic amines, which could represent a risk for consumers. Furthermore, Lev. brevis, being a heterofermentative lactic acid bacteria (LAB), also produced ethanol, acetic acid, and a variation in the sausage colour. The production of biogenic amines was confirmed in vitro. Furthermore, as observed in a previous study, the second cause of spoilage can be attributed to moulds which grew during ripening; both the isolated strains, Penicillium nalgiovense, added as a starter culture, and P. lanosocoeruleum, present as an environmental contaminant, grew between the meat and casing, producing a large amount of total volatile nitrogen, responsible for the ammonia smell perceived in the ripening area and in the sausages. This is the first description of Levilactobacillus brevis predominance in spoiled goose sausage.
ALTERNATIVE TECHNIQUE OF PANCREATICOGASTROSTOMY AFTER PANCREATICODUODENECTOMY A REGIONAL CANCER CENTRE STUDY.

Mohit Sharma 1 , Ketul puj 2 , Hemkant verma 2 and Shashank J. Pandya 3 . 1. Associate Professor, Department of Surgical Oncology Gujarat Cancer And Research Institute (G.C.R.I.), Ahmedabad. 2. Resident Doctor, Department of Surgical Oncology Gujarat Cancer And Research Institute (G.C.R.I.), Ahmedabad. 3. Professor, Department of Surgical Oncology Gujarat Cancer And Research Institute (G.C.R.I.), Ahmedabad. Manuscript Info Abstract . Manuscript History
Complete mitochondrial genome of Eonemachilus longidorsalis (Cypriniformes: Nemacheilidae): genome characterization and phylogenetic consideration

Abstract For the first time, this study presents the complete mitochondrial genome and phylogenetic analysis of Eonemachilus longidorsalis, an endemic species in southwest China. The mitogenome is a circular molecule of 16,569 bp in length with a base composition of 30.2% A, 27.3% T, 16.6% G, and 25.9% C. The phylogenetic analysis based on the complete mitogenomes shows that E. Longidorsalis clusters with Yunnanilus jiuchiensis, Yunnanilus pleurotaenia and Eonemachilus niger. This contribution may provide a valuable framework for completely resolving phylogenetic relationships of the family Nemacheilidae in future research.
Genetic characteristics and integration specificity of Salmonella enterica temperate phages

Introduction Temperate phages can engage in the horizontal transfer of functional genes to their bacterial hosts. Thus, their genetic material becomes an intimate part of bacterial genomes and plays essential roles in bacterial mutation and evolution. Specifically, temperate phages can naturally transmit genes by integrating their genomes into the bacterial host genomes via integrases. Our previous study showed that Salmonella enterica contains the largest number of temperate phages among all publicly available bacterial species. S. enterica is an important pathogen that can cause serious systemic infections and even fatalities. Methods Initially, we extracted all S. enterica temperate phages from the extensively developed temperate phage database established in our previous study. Subsequently, we conducted an in-depth analysis of the genetic characteristics and integration specificity exhibited by these S. enterica temperate phages. Results Here we identified 8,777 S. enterica temperate phages, all of which have integrases in their genomes. We found 491 non-redundant S. enterica temperate phage integrases (integrase entries). S. enterica temperate phage integrases were classified into three types: intA, intS, and phiRv2. Correlation analysis showed that the sequence lengths of S. enterica integrase and core regions of attB and attP were strongly correlated. Further phylogenetic analysis and taxonomic classification indicated that both the S. enterica temperate phage genomes and the integrase gene sequences were of high diversities. Discussion Our work provides insight into the essential integration specificity and genetic diversity of S. enterica temperate phages. This study paves the way for a better understanding of the interactions between phages and S. enterica. By analyzing a large number of S. enterica temperate phages and their integrases, we provide valuable insights into the genetic diversity and prevalence of these elements. This knowledge has important implications for developing targeted therapeutic interventions, such as phage therapy, to combat S. enterica infections. By harnessing the lytic capabilities of temperate phages, they can be engineered or utilized in phage cocktails to specifically target and eradicate S. enterica strains, offering an alternative or complementary approach to traditional antibiotic treatments. Our study has implications for public health and holds potential significance in combating clinical infections caused by S. enterica.
Multivariate generalized Birnbaum—Saunders kernel density estimators

ABSTRACT In this article, we first propose the classical multivariate generalized Birnbaum–Saunders kernel estimator for probability density function estimation in the context of multivariate non negative data. Then, we apply two multiplicative bias correction (MBC) techniques for multivariate kernel density estimator. Some properties (bias, variance, and mean integrated squared error) of the corresponding estimators are also investigated. Finally, the performances of the classical and MBC estimators based on family of generalized Birnbaum–Saunders kernels are illustrated by a simulation study.
Optimal Teicoplanin Dosage Regimens in Critically Ill Patients: Population Pharmacokinetics and Dosing Simulations Based on Renal Function and Infection Type

Purpose To develop a population pharmacokinetic model describing teicoplanin concentrations in patients hospitalized in intensive care unit (ICU) and to perform Monte Carlo simulations to provide detailed dosing regimens of teicoplanin. Methods This single-center, prospective, observational study was conducted on 151 patients in ICU with 347 plasma samples. The population pharmacokinetics model was established and various covariates were evaluated. The probability of target attainment (PTA) of various proposal dosing regimens was calculated by Monte Carlo simulations. Results The two-compartment model adequately described teicoplanin concentration-time data. The estimated glomerular filtration rate (eGFR) associated with systemic clearance (CL) was the only covariate included in the final model. The estimate of CL was 0.838 L/h, with the eGFR adjustment factor of 0.00823. The volume of the central compartment (Vc), inter-compartmental clearance (Q) and volumes of the peripheral compartments (Vp) were 14.4 L, 3.08 L/h and 51.6 L, respectively. The simulations revealed that the standard dosage regimen was only sufficient for the patients with severe renal dysfunction (eGFR ≤ 30 mL/min/1.73 m2) to attain target trough concentration (Cmin, PTA 52.8%). When eGFR > 30 mL/min/1.73 m2, increasing dose and the administration times of loading doses were the preferred options to achieve target Cmin based on the renal function and types of infection. Conclusion The most commonly used standard dosage regimen was insufficient for all ICU patients. Our study provided detailed dosing regimens of teicoplanin stratified by eGFR and types of infection for ICU patients.