Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation of the Greedy Algorithm to determine the nearest route Search in distributing food production

Distribution is the activity of allocating goods from producers to customers within allocated time. Managing product distribution is very important for the survival of a company, yet improper planning and management will cause the production is stacked in the warehouse thus this will cause unhealthy financial cycles and turnover to the company itself. Nowadays many companies produce foodstuffs but one of the major problems faced by the companies are the delays in distributing food production. It is found that the common difficulty faced by the food production companies in distributing the product due to long travelling distance, traffic congestion, natural disasters, ambiguous routes as well as unstructured routes. To overcome the problems, greedy algorithm is implemented. The algorithm able to identify the optimal pathway and time consumption by finding the closest distance, followed by the utmost distance. Therefore this will reduce the cost of distribution and other company resources. The results of this study show that the algorithm identifies Route 5 as the best route. This is because it will go through 5 cities, namely A-B-C-F-G-H with distance of 648KM. Although it is considered as long travelling distance, on the other hand the algorithm suggests that 648KM is the optimum distance to travelling to city H.
Large visible-light-driven photostriction in Bi(Ni2/3Nb1/3)O3–PbTiO3 ferroelectrics

Photostrictive effect that has been discovered for over half a century is getting renewed interest in recent years in view of the great potentials for optomechanical applications. Ferroelectric materials represented by lead lanthanum zirconated titanate have been widely studied in this field because of their relatively large photostriction and fast photoresponse, but their wide bandgaps with limit response to visible light hinder further practical application. Here, visible-light-driven photostrictions of the order of 10−3 are discovered in Bi(Ni2/3Nb1/3)O3–PbTiO3 (BNNPT) ferroelectric solid solutions. Three BNNPT compositions with different phase structures, exhibiting notably different piezoelectric and photovoltaic properties, are selected to conduct the photostriction investigation, and their analogous photostrictive behaviors contradict with previous acknowledgment that the photostriction of ferroelectrics originates from the photovoltage-induced inverse piezoresponse. The nonuniform shifts of the XRD diffraction peaks under external laser illumination and the redshifts of the laser power dependent Raman modes disclose that the photostriction is mainly attributed to the light-induced distortion of BO6 octahedra. This study sheds insight into the mechanism of the photostriction of ferroelectrics.
Much does not help much: 3D pareto front of safety, comfort and energy consumption for an active pneumatic suspension strut

With regard to autonomous driving the demands on comfort are increasing. This makes it attractive to use active suspension systems. The system developed at TU Darmstadt is able to increase driving comfort up to 28 % while maintaining driving safety compared to a passive suspension system. This paper investigates the influence of available energy and power of the active system. The investigation is based on a simulation of a quarter car model and an uneven country road. This paper shows that the more energy the active system has at its disposition, the greater is the range between a comfortable and a sporty chassis. Furthermore the driving comfort can be increased by 28 % with constant driving safety. The average power required for this is 15 W and the maximum power is 300 W.
The effects of vitamin D supplementation on healthy and hypercholesterolemic rabbits on levels of OSI and paraoxonase

Abstract Objective Conflicting data are available in literature regarding the effects of vitamin D (VitD) supplementation diet on lipid panel. Therefore, we had the purpose to evaluate the effects of VitD supplementation on lipid panel by a controlled experimental study, and those of VitD supplementation on oxidative stress index (OSI) and paraoxonase-1 (PON1) values in healthy and hypercholesterolemic male rabbits. Methods Thirty New Zealand rabbits were randomly separated into control, VD, HC+VD and HC groups. Control and VD groups were fed with standard chow, whereas HC+VD and HC groups were fed with 0.5% cholesterol chow a period of 8 weeks. During this period, VD and HC+VD groups were orally administered with 300 IU/kg/day VitD. Results The increase in serum total cholesterol (TC) and OSI level of HC group were significant compared to those in HC+VD group. Decreases in serum HDL-cholesterol (HDL-C) and TC levels of VD group were significant within the groups. Conclusion Without any doubt it is important that applied VitD level should be in the ideal range for healthy living. However, it is also necessary to increase the serum HDL-C level (and hence PON1), which is decreases as a result of VitD supplementation. Therefore, we believe that during VitD supplementation, regular physical activity should be performed to increases serum HDL-C.
Assisting End Users in Workflow Systems

In today's society, almost every company and institution employs some kind of workflow automation. Hospitals employ software that automates health care processes. The coastal guard uses workflow software to assist in search and rescue operations. Naval ships use workflow automation software to manage people, resources and mission goals. Before automation, users knew the process by heart, and knew how their choices influenced the process. Workflow systems hide the flow of processes behind interfaces. For end users, it is not always clear how decisions influence the progress of a task. Another factor in the decision process of an end user is the information available. How can a user be sure that he or she took all information into consideration before reaching a decision? One way to provide users with more information about their current situation is to provide them with next-step hints. These hints are based on their current situation: their position in the workflow and the data in the system. In this dissertation, I attempt to answer the question, how can we provide end users with next-step hints to aid them in making decisions? The answer to that question is found by applying of techniques from intelligent tutoring systems (ITS) and program analysis. Previous work on ITS strategies inspired the first approach to generate next-step hints. By extending the original program with additional information, it can be viewed as a rule-based problem, making it susceptible to generic AI search and solving algorithms. The second approach comes from program analysis. By employing symbolic execution, next-step hints are automatically calculated, without any changes to the original code. The application of both techniques results in two next-step hints systems. One system, aided by the programmer, the other fully automatic. In developing the automatic system, a formal Task-oriented Programming semantics is also developed, including a symbolic execution semantics. Both systems are proven to be sound and complete. They are both implemented, too, showing that they work in practice. Providing next-step hints to end users is crucial in improving the quality of decisions. It helps end users by giving insight into the effects of their choices, and makes sure that all data is taken into consideration.
Dissolved organic carbon concentration and denitrification capacity of a hill country sub-catchment as affected by soil type and slope

ABSTRACT Characterising the dissolved organic carbon (DOC) concentration and denitrification capacity of the soils and slopes in hill country is important in order to manage the leaching and availability of nitrate in ground and surface waters. This study investigated the DOC concentration and denitrification capacity of the soils and slope classes of a sub-catchment within a hill country farm, in Palmerston North, New Zealand. Fifty locations comprising of 2 soil orders (Pallic, Brown), 8 soil types (3 drainage classes) and 3 slope classes were sampled from different soil depths down to 1 m. The results suggest that compared to slope, soil type had a greater effect on denitrification capacity within the sub-catchment. The Ramiha soil had the highest DOC concentration (105 mg kg−1 within 0.3–0.6 m depth) and moisture content, and hence the highest denitrification capacity (10 µg kg−1 h−1). This suggests that farms or catchments with similar soil types may have a greater capacity to attenuate nitrogen losses to the environment.
Using concept maps to characterise cellular respiration knowledge in undergraduate students

ABSTRACT Meaningful learning occurs by relating new information to and revising prior knowledge, making it essential to understand student knowledge before helping them move toward a more scientific understanding. In this study, we characterise prior knowledge about cellular respiration in undergraduate students enrolled in introductory biology by analysing student-constructed concept maps (N = 182) and interviews (N = 9). Students were instructed to create concept maps from a bank of 20 concepts with the purpose of interconnecting the processes of cellular respiration, showing how pools of ATP are generated and used, and identifying where the events of cellular respiration occur. Student maps were analysed for content, quality and organisation of knowledge. Interviews were used to corroborate inferences made from concept maps. Students had a simplified understanding of cellular respiration and its processes as evident by cognitive structures with limited quantities of schemas that were vaguely connected and linearly organised. Furthermore, students had a better understanding of glycolysis than fermentation. Instructors can use these findings to help students build better knowledge of cellular respiration by focusing on incorporating relevant schemas, creating quality connections among schemas, and organising their knowledge of cellular respiration to reflect biological complexity.
Language evolution research in the year 2020: A survey of new directions

This introductory paper reviews recent advances in language evolution research and summarizes the contributions of the special issue “New Directions in Language Evolution Research” in the broader context of these developments. Specifically, we discuss the increasing role of multimodality and iconicity, the more integrative view of language dynamics that has arguably broadened the scope of language evolution research, and recent methodological innovations that allow for a more fine-grained study of e.g. typological distributions or behavioral patterns that can give clues to some of the keyquestions discussed in the field.
Validating the dance fundamental movement skills assessment for balance

ABSTRACT The Dance Fundamental Movement Skills Assessment (DFMS-A) examines fundamental movement skills as described by Footprints Dance Project in their teaching resource: Footprints Movement Tool. It was designed to inform teaching practice, highlighting students’ strengths and weaknesses. In addition to providing holistic assessment for the whole dancer, the DFMS-A provides an extended score range encompassing the higher level of corporal expectation demanded of dancers, as opposed to pass/fail metrics (normal/abnormal). The current study aims to evaluate the validity and reliability of the balance component of the DFMS-A using a sample population from the University. The DFMS-A was compared with three standard physical assessments of balance: Y balance test, Single Leg Stance (SLS) test, and Functional reach test. Pearson Correlations demonstrated significant correlations between the DFMS-A and Y balance and SLS tests respectively (r = 0.745–0.974; p < 0.008), with minimal correlation found with the Functional Reach test. Intra-rater reliability was tested 1.5 years after the original assessment was completed, and demonstrated high reliability (>85%). These positive results support the use of the DFMS-A as a comprehensive balance assessment with more depth than current tests, suggesting it may warrant further testing in other aspects of functional movement such as weight transfer and body alignment.
Usage and Impact of Artificial Intelligence on Accounting: 213 Evidence from Malaysian Organisations

Purpose: With the embedment of Artificial Intelligence (AI) technology into the accounting software, accounting function entered another phase of evolution in terms of the working method. By integrating the AI-based accounting software into the operational tasks, the functions of account payables and account receivables become easy and efficient. Despite the tremendous advantages of AI, the adoption of AI in Malaysia is still low relatively compare to other countries. Furthermore, there are limited academic research performed to study the impact of AI adoption on the organisations especially from the accounting perspective. Therefore, this study aims to investigate the use and impact of AI-based accounting software in organizations. Methodology: Face-to face in-depth semi structure interviews were conducted among nine organizations that are using AI based accounting software. The representatives who participated in the interviews were from the accounting service division of the respective organisation. Constant comparative method was used to analyse the data collected. Finding: The study found the usage of the AI-based accounting software has proved to have significant impact on the organisations in terms of increased productivity, improved efficiency, improved customer service, flexible working style, process governance and manpower saving. Originality: AI has emerged as a disruption technology in the era of Industry 4.0. This research has studied on the implication of AI adoption in the accounting function. From the result of this study, it has evidenced that adoption of AI-based accounting software in account payable function has yielded positive impact to the organisations. The finding will to spur the confidence of the organisations in Malaysia to invest in the AI technology.
The Mediating Role of Intellectual Capital in Open Innovation in the Service Industries

The paper intends to examine the mediating role of intellectual capital in the relation between the openness of service companies’ search strategies and thr innovation performance. It models the relationship between external search strategies of open innovation and proposes how intellectual capital matters for openness strategies in the service industries. Moreover, the paper intends to expand the field of open innovation through exploring the mediating effect of intellectual capital. This paper fulfills an identified need to study how intellectual capital can be enabled in the open innovation of the service industries. Both Hierarchical Multiple Regression and the Structural Equation Model were employed to test the innovation model by the panel data of the second Taiwan Innovation Survey including 948 service firms. Empirical insights enable us to have a better understanding in terms of how service companies learn from external knowledge sources. This paper suggests that the impact of openness strategies on innovation performance becomes indirect through the partial mediator of intellectual capital so that innovation performance in service industry benefits from simultaneously incorporating intellectual capital with the efficient openness strategies. Finally, the paper includes implications for more insights into how service companies improve their innovative activities with external searching strategies and practices in terms of intellectual capital.
Time-Dependent Downscaling of PM2.5 Predictions from CAMS Air Quality Models to Urban Monitoring Sites in Budapest

Budapest, the capital of Hungary, has been facing serious air pollution episodes in the heating season similar to other metropolises. In the city a dense urban air quality monitoring network is available; however, air quality prediction is still challenging. For this purpose, 24-h PM2.5 forecasts obtained from seven individual models of the Copernicus Atmosphere Monitoring Service (CAMS) were downscaled by using hourly measurements at six urban monitoring sites in Budapest for the heating season of 2018–2019. A 10-day long training period was applied to fit spatially consistent model weights in a linear combination of CAMS models for each day, and the 10-day additive bias was also corrected. Results were compared to the CAMS ensemble median, the 10-day bias-corrected CAMS ensemble median, and the 24-h persistence. Downscaling reduced the root mean square error (RMSE) by 1.4 µg/m3 for the heating season and by 4.3 µg/m3 for episodes compared to the CAMS ensemble, mainly by eliminating the general underestimation of PM2.5 peaks. As a side-effect, an overestimation was introduced in rapidly clearing conditions. Although the bias-corrected ensemble and model fusion had similar overall performance, the latter was more efficient in episodes. Downscaling of the CAMS models was found to be capable and necessary to capture high wintertime PM2.5 concentrations for the short-range air quality prediction in Budapest.
Identifying loci under positive selection in complex population histories

Detailed modeling of a species’ history is of prime importance for understanding how natural selection operates over time. Most methods designed to detect positive selection along sequenced genomes, however, use simplified representations of past histories as null models of genetic drift. Here, we present the first method that can detect signatures of strong local adaptation across the genome using arbitrarily complex admixture graphs, which are typically used to describe the history of past divergence and admixture events among any number of populations. The method—called Graph-aware Retrieval of Selective Sweeps (GRoSS)—has good power to detect loci in the genome with strong evidence for past selective sweeps and can also identify which branch of the graph was most affected by the sweep. As evidence of its utility, we apply the method to bovine, codfish and human population genomic data containing multiple population panels related in complex ways. We find new candidate genes for important adaptive functions, including immunity and metabolism in under-studied human populations, as well as muscle mass, milk production and tameness in specific bovine breeds. We are also able to pinpoint the emergence of large regions of differentiation due to inversions in the history of Atlantic codfish.
Unc 51–like autophagy-activating kinase (ULK1) mediates clearance of free α-globin in β-thalassemia

Erythroid maturation is coordinated to maximize the production of hemoglobin A heterotetramers (α2β2) and minimize the accumulation of potentially toxic free α- or β-globin subunits. In β-thalassemia, mutations in the β-globin gene cause a build-up of free α-globin, which forms intracellular precipitates that impair erythroid cell maturation and viability. Protein quality-control systems mitigate β-thalassemia pathophysiology by degrading toxic free α-globin. We show that loss of the Unc 51–like autophagy-activating kinase gene Ulk1 in β-thalassemic mice reduces autophagic clearance of α-globin in red cell precursors and exacerbates disease phenotypes, whereas inactivation of the canonical autophagy gene Atg5 has minimal effects. Systemic treatment with rapamycin to inhibit the ULK1 inhibitor mTORC1 reduces α-globin precipitates and lessens pathologies in β-thalassemic mice, but not in those lacking Ulk1. Similarly, rapamycin reduces free α-globin accumulation in erythroblasts derived from β-thalassemic patient CD34+ hematopoietic progenitors. Our findings identify a new, drug-regulatable pathway for ameliorating β-thalassemia. One Sentence Summary Rapamycin alleviates β-thalassemia by stimulating ULK1-dependent autophagy of toxic free α-globin.
Organic dye anchor peptide conjugates as an advanced coloring agent for polypropylene yarn

Polypropylene as one of the world's top commodity polymers is also widely used in the textile industry. However, its non-polar nature and partially crystalline structure significantly complicate the process of industrial coloring of polypropylene. Currently, textiles made of polypropylene or with a significant proportion of polypropylene are dyed under quite harsh conditions, including the use of high pressures and temperatures, which makes this process energy intensive. This research presents a three-step synthesis of coloring agents, capable of adhering onto synthetic polypropylene yarns without harsh energy-consuming conditions. This is possible by encapsulation of organic pigments using trimethoxyphenylsilane, introduction of surface double bonds via modification of the silica shell with trimethoxysilylpropylmethacrylate and final attachment of highly adhesive anchor peptides using thiol-ene chemistry. We demonstrate the applicability of this approach by dyeing polypropylene yarns in a simple process under ambient conditions after giving a step-by-step guide for the synthesis of these new dyeing agents. Finally, the successful dyeing of the yarns is visualized, and its practicability is discussed.
Generating Animations from Instructional Text

Generating animations from text finds application in numerous areas like screenplay writing, instructional videos, public safety, and video user manuals, etc. However, translating natural language text into animations is a challenging task. We develop a text-to-animation system which can handle any simple instructional text. We have created an NLP pipeline to extract action sequences from cooking recipes and map them to appropriate atomic actions present in the system’s knowledge base. This paper explores a novel approach of linking Graphics with Natural Language Processing (NLP). Our goal is to obviate the necessity of having a large collection of stored graphics.
Isolation and Characterization of Nanobodies against a Zinc-Transporting P-Type ATPase

P-type ATPases form a large and ubiquitous superfamily of ion and lipid transporters that use ATP (adenosine triphosphate) to carry out their function. The IB subclass (PIB-ATPases) allows flux of heavy metals and are key players in metal detoxification, critical for human health, crops, and survival of pathogens. Nevertheless, PIB-ATPases remain poorly understood at a molecular level. In this study, nanobodies (Nbs) are selected against the zinc-transporting PIB-ATPase ZntA from Shigella sonnei (SsZntA), aiming at developing tools to assist the characterization of the structure and function of this class of transporters. We identify six different Nbs that bind detergent stabilized SsZntA. We further assess the effect of the Nbs on the catalytic function of SsZntA, and find that five nanobodies associate without affecting the function, while one nanobody significantly reduces the ATPase activity. This study paves the way for more refined mechanistical and structural studies of zinc-transporting PIB-ATPases.