Miracle-dz/UniFAR-FTUs huggingface dataset:
THE EFFECT OF ADDING DIFFERENT LEVELS OF NANO AND NON-NANO ZINC OXIDE TO THE DIET ON PHYSIOLOGICAL TRAITS OF SOME BROILERS

This study was conducted at the Poultry Research Station / Agricultural Research Office/Ministry of Agriculture, for the period from 3/8/2019 to 13/10/2019 to study the effect of adding different levels of Nano and non-Nano zinc oxide to broiler diets on production performance and some physiological traits. 420 unsexed one-day-old chicks (Ross308) were used in the experiment with an average weight of 36 g, the chicks were distributed randomly into 7 treatments, each one included 4 replicates by 15 chicks per replicate. The experimental treatments were as follows: T1 control treatment without adding zinc, T2, T3, and T4 adds Nano zinc oxide at a concentration of 10, 30, and 50 mg/kg feed for the treatments, respectively, and T5, T6, and T7 adding Non-Nano zinc oxide at a concentration of 10, 30 and 50. mg/kg feed for treatments, respectively. The experimental results indicated that there was a significant superiority (P <0.05) was occurring in blood zinc concentration at 42 days of treatment T6 compared with T1, T3, and T7. As well as, treatment T2 and T6 were superior compared to treatment T7 in the triglyceride level at 42 days, moreover a significant superiority (P <0.05) was observed in infectious bronchitis (IB) titer at treatment T4 compared to the rest of the treatments. Finally, a significant superiority (P <0.05) was observed at treatment T2 and T3 compared to T4 in zinc concentration in the thigh as well as its increase in the kidneys at treatment T3 compared to T2, T4, T5, and T7.
Financial Reporting and the Accounting Expectations Gaap

The overall goal of financial reporting is to provide high quality financial information regarding reporting entities that is useful for informed decision making. Considering most organizations have multiple groups of stakeholders which often have differing and competing informational needs, as well as expectations and desired outcomes, the accounting expectations gap has become a topic of current debate in many business circles. Historically, the accounting expectations gap has centered around the role of the auditor and audit responsibility. The financial accounting expectations gap encompasses what the preparers of the statements and auditors believe they should contain and includes what stakeholders believe the financial statements should contain. The purpose of this paper is to extend and apply existing literature to the financial reporting expectations gap and bridge the gap in between the two approaches. The conclusions, recommendations, and implications reached are generalizable and appropriate for use in developing best practice solutions.
Failure of polymer solution filaments

The laws of thinning and breaking of a capillary filament of a high-molecular-weight polymer solution were experimentally and theoretically investigated. Physical mechanisms involved in the filament breaking are analyzed. Measurement of the time variation of the capillary filament diameter, performed for a variety of polymer solutions, gave results consistent with the theoretical model developed. The possibilities to use observations of the formation, thinning, and breakage of polymer filaments for evaluation of the rheological characteristics of polymer solutions are discussed.
Edge-Based Runtime Verification for the Internet of Things

Complex distributed systems such as the ones induced by Internet of Things (IoT) deployments, are expected to operate in compliance to their requirements. This can be checked by inspecting events flowing throughout the system, typically originating from end-devices and reflecting arbitrary actions, changes in state or sensing. Such events typically reflect the behavior of the overall IoT system – they may indicate executions which satisfy or violate its requirements.
Gibbs PRAMpling

Gibbs sampling is a Markov chain Monte Carlo method used to approximate joint distributions that are difﬁcult to sample from and intractable to compute directly. Optimizing the execution speed of Gibbs sampling is a large area of active research since it is a highly general and widely used algorithm. In this paper, we present several parallel Gibbs sampling approaches for estimating the parameters of Bayesian Gaussian mixture models. We analyze their complexity on parallel RAM architectures, and compare asymptotics with experimental wall-clock performance.
Światło w architekturze i urbanistyce – niedoceniane spoiwo miasta

The city consists of houses, buildings, squares, streets, green spaces. Each urban element has its place and meaning. These elements enhanced by lighting gain additional value: the mutual relationships changes, some gain importance or start to inflect certain impact on the users. There are three main lighting groups: lighting for safety, advertising and aesthetic illumination that co-create the image of the city at night. The quality and quantity of lighting has a decisive influence on the perception of safety and spatial orientation. At night, light can enhance and frame city's characteristic views, creating new panoramic experiences. Lighting in urban areas requires very careful planning, because in addition to its safety role it can also significantly affect the physical experiences and the mood of the inhabitants. Currently applied lighting typology and solutions do not consider the psychological comfort of the communities. Poorly planned lighting causes three types of issues: aesthetic, ecological and physical and psychological. Inadequate and badly planned lighting can create visual chaos, increase light pollution and its 'night-interference' in residential zones may increase visual discomfort experienced by the residents, disturbing the circadian cycle. The main requirement for a successful integration of the city through the light relies on devising comprehensive lighting design programmes, which will include the various rules and guidelines for lighting. The next crucial stage would be the consistent implementation of the devised plan.
Factors Influencing e-Government Adoption (A Case Study of Information System Adoption in PPATK) (Faktor-faktor yang Memengaruhi Adopsi e-Government (Studi Kasus Adopsi Sistem Informasi di PPATK))

Information Communication Technology (ICT) has encouraged e-government implementation to improve government institution performance in society, business and fellow government institutions. Many Information Systems (IS) are created and used, but not all of them are successful. This is contrary to the expectations that were mentioned earlier. Therefore, it is necessary to conduct research to identify factors that influence e- government adoption. This paper presents a case study of information system adoption in a government institution. The study was conducted using TOE methods. Data were collected using qualitative method and subsequently processed using Qualitative Data Analysis tools. Results indicated that all factors analyzed in TOE framework influenced IS adoption. However, not all factors were properly conducted. Therefore, they need to be developed to address difficulties in IS adoption so it will meet the e-government implementation expectation.
Exploring the Characteristics of Millennials in Online Buying Behavior

Online Shopping has become an important medium for sales and marketing transaction. In fact, many people are switching from the traditional form of trading goods and now joining the Online Shopping craze. Businesses are taking advantage of this opportunity to introduce their products to the market and to expand their reach. Philippines is the third highest in the Asia Pacific countries which was seen patronizing the platform of buying products online. However, it was also perceived that there is a high percentage of Filipino buyers who are not a fan of Online Shopping. This research studied and explored the factors that affect the buying behavior of the consumers and aimed to investigate the relationship of the factors of online shopping and the consumer purchase decision process. The researcher settled to use the descriptive research approach using random sampling to see the current situation of “what it is” today. The results revealed that consumers consider the factors such as Sales promotion, Advertisement, Social environment, Feedback, Logistics, and Payment process and that they undergo process of Consumer Purchase decision making. Using Pearson Correlation Coefficient or Pearson’s R the researchers found out that there is a significant relationship on the factors in online shopping and Consumer Purchase Decision Process. Thus, online business must take into consideration these factors in designing and implementing their online shops to experience sales growth.
Hand and Finger Fracture Detection and Type Classification Using Image Processing

The current research introduces a novel method for fracture detection and classification. The basic stages of fracture detection includes preprocessing of bone image and morphological operations to obtain the ROI region which is manipulated by a post processing stage to remove non-fracture pixels. The suggested approach extract three features from bone image which are transverse, cracks and divergence features in order to define the fracture type or integrity of bone image. The designed systems detect the different fracture types correctly beside the hybrid fracture type. We applied experiments on a dataset consisting of 155 bone images including 100 fracture images, 30 hand-fingers images and 25 normal images. The systems achieved 92% true detection rate for general bone fractures, 93.33% true detection rate for finger bone fractures and 93.33% true rejection rate. The experiments showed that the inner false detection rates between each type and the others are less than 4%.
Inter-domain transfer learning for Semantic segmentation of Peripheral Zone of Prostate.

Segmentation of the prostate zones, including the peripheral zone (PZ) and the transition zone (TZ), from magnetic resonance imaging (MRI) is a key part of the image based prostate cancer diagnosis and management. Among various segmentation methods, deep learning based semantic segmentation methods have drawn increasing attention in recent years due to their effectiveness compared with manual or traditional atlas-based methods. However, this method possesses two common limitations: class imbalance and sub-optimal feature extraction from noisy images. In this paper, we propose an Inter-Domain Transfer Learning (IDTL) method to alleviate these limitations in order to segment the PZ of the prostate with a better accuracy. We improve the generalization ability of the deep learning model by pretraining it to segment the entire prostate first before training to segment the PZ. Results show that the deep learning model, pretrained on segmenting the entire prostate first, results in a greater accuracy of PZ segmentation. The accuracy improves further when an additional prostate MRI dataset is included in the pretraining. This improvement in accuracy is true for each fold of the 10-fold cross validation and each patient of the main dataset, which evidences the effectiveness of the proposed method. We report cases where the deep learning model yields poor segmentation accuracy to identify causes and solutions in the limitations of our proposed model.
A silane primer : chemistry and applications of alkoxy silanes

Formulators in the paint, ink, adhesives, water repellents, and other related industries require materials that resist peeling and penetration in spite of prolonged exposure to heat, cold, moisture, and chemical attack. Research into these problems resulted in the development of alkoxy functional silanes for use as adhesion promoters, crosslinkers, and hydrophobes. The intent of this paper is to briefly review the unique chemistry of this class of materials and to discuss three areas of product development that have benefitted from the utilization of silanes: surface treatment, additive, and reactive intermediate. This discussion will include recommendations for specific organic/silane combinations.
Spontaneous Melodic Productions of Expert Musicians Contain Sequencing Biases Seen in Language Production

Language production involves complex action sequencing to produce fluent speech in realtime, placing considerable constraints on working memory that lead to sequencing biases in production. Researchers have speculated that these biases may extend beyond language to other human behaviors involving action sequencing, but this claim has not been empirically investigated. Here we provide a strong test of this hypothesis, examining whether biases seen in language production also constrain one of the most complex and spontaneous human behaviors: musical improvisation. Using a large corpus of improvised solo transcriptions from eminent jazz musicians, we test for the existence of an established production bias observed in language production termed easy first—a tendency for more accessible sequences to occur at the beginning of a phrase, allowing incremental planning of more complex phrases. Our analysis shows consistent evidence of easy first in improvised music. We find that the beginning of improvised musical phrases contains 1) more frequently occurring interval patterns, 2) smaller intervals, 3) less interval variety, 4) less pitch variety, and 5) fewer direction changes. There was no easy first bias in a control corpus containing simulated data with the same structure, indicating that the effects are specific to real-time melodic production and not simply due to stylistic conventions. The findings indicate that even expert jazz musicians, known for spontaneous creative performance, reliably retrieve easily-accessed melodic sequences before creating more complex sequences—consistent with an incremental planning strategy employed in language production—suggesting that similar biases constrain the spontaneous production of music and language. Charles Darwin famously observed that “the capacity of producing musical notes. must be ranked amongst the most mysterious with which (man) is endowed” [7]. While Darwin was concerned with understanding the adaptive significance of music, a fundamentally similar state of uncertainty also shrouded the cognitive underpinnings of music production. Insight into both of these issues would finally arrive 80 years later when Karl Lashley suggested that all complex sequential actions require hierarchical planning [9, 22]. Thus, the underpinnings of both music and language production share common origins, both phylogenetic and cognitive, with hierarchical action plans. While this view has generally been endorsed [22], there has been virtually no evidence supporting the notion that common cognitive processes underlie the spontaneous production of music and language. Studying the potential link between language and music production may yield insights into how humans differ from other species. We begin to tackle this longstanding issue by investigating whether one of the cognitive biases known to influence word ordering choices in speech production also manifests to constrain sequencing in the context of spontaneous music production.
Investigating the loads and performance of a model horizontal axis wind turbine under reproducible IEC extreme operational conditions

Abstract. The power generation and loading dynamic responses of a 2.2 m diameter horizontal axis wind turbine (HAWT) under some of the IEC 61400-1 transient extreme operational conditions, more specifically extreme wind shears (EWSs) and extreme operational gust (EOG), that were reproduced at the WindEEE Dome at Western University were investigated. The global forces were measured by a multi-axis force balance at the HAWT tower base. The unsteady horizontal shear induced a significant yaw moment on the rotor with a dynamic similar to that of the extreme event without affecting the power generation. The EOG severely affected all the performance parameters of the turbine.
CHAPTER 1:The Principles of Magnetic Resonance, and Associated Hardware

This chapter links the basic principles of magnetic resonance with the relevant hardware components in a magnetic resonance system. These components include the magnet, radiofrequency coil(s), radiofrequency amplifier, shim coils, magnetic field gradient coils, gradient amplifiers, frequency locking circuitry, and receiver. The role of each component is explained in terms of its relationship to the associated magnetic resonance phenomenon, e.g. nuclear polarization, resonance frequency, precession, the effect of radiofrequency pulses, relaxation and spatial encoding. The requirements of each of the hardware components are quantified for experiments in three different “domains”: high-resolution liquid-state nuclear magnetic resonance spectroscopy, magic-angle spinning solid-state nuclear magnetic resonance spectroscopy, and magnetic resonance imaging. Finally, an Appendix is included, which contains details of two mathematical frameworks, namely spherical harmonics and the Biot–Savart law, used in the design of magnets, shim coils, magnetic field gradients and RF coils throughout the book.
The design of an efficient class E-LCCL capacitive power transfer system through frequency tuning method

In this work, the optimum zero voltage switching (ZVS) of Class E-LCCL capacitive power transfer (CPT) was determined via frequency tuning method. Through this an efficient system can be guanranteed although there is a change in the capacitive plates distance. This study used a Class-E LCCL inverter, as it can operate at a high alternate current frequency, besides producing low switching losses and minimal power losses. Specifically, this study conducted simulations and experiments to analyse the performance of an LCCL CPT System at 1 MHz operating frequency and 24 V DC supply voltage. Using an air gap distance of 0.1 cm, the designed CPT system prototype successfully achieved an output power of 10W and an efficiency of 95.45%. This study also found that by tuning the resonant frequency of the Class E-LCCL system, the optimum ZVS can be obtained although capacitive plate distance was varied from 1-3 cm via experimental. The results of this study could benefit medical implant and portable device development, consumer electronics, and environments that involve electrical hazards.
Efficacy of zinc oxide nanoparticles on hepatocellular carcinoma-induced biochemical and trace element alterations in rats

Samir A. E. Bashandy1*, Omar A. H. Ahmed-Farid2, Sherif Abdelmottaleb Moussa3, Enayat A. Omara4, Gehad A. Abdel Jaleel1, Fatma A. A. Ibrahim3 1Pharmacology Department, National Research Centre, Cairo, Egypt. 2Physiology Department, National Organization for Drug Control and Research, Cairo, Egypt. 3Biophysics Group, Department of Biochemistry, Genetic Engineering and Biotechnology Division, National Research Centre, Cairo, Egypt. 4Pathology Department, National Research Centre, Cairo, Egypt.
A proposed model for frequency tuned antennas used in mobile communication systems

The antenna is considered as one of the most fundamental elements in wireless communication systems, especially in mobile devices. Desirable specifications of antennas include covering wide range of operating frequencies, while maintaining high quality of system performance over the whole range of operating frequencies. Therefore, the ability of tuning the resonant frequency of the antenna without altering its physical dimensions would be highly recommended in up-and-coming designs of antennas in mobile devices. This research work proposes a model for tuning the operating frequency of the inverted F-antenna over a reasonably wide range of frequencies, via altering the electromagnetic properties of its ferrite material. In this proposed model, it will be shown that the electronic control of the permeability of the ferrite material of the antenna leads effectively to a significant shift in its resonant frequency, and hence to an overall improvement in the performance of the communication system.
Multi-kernel CNN block-based detection for COVID-19 with imbalance dataset

COVID-19, which originated from Wuhan, rapidly spread throughout the world and became a public health crisis. Recognizing the positive cases at the earliest stage was crucial in order to restrain the spread of this virus and to perform medical treatment quickly for patients affected. However, the limited supply of RT-PCR as a diagnosis tool caused greatly delay in obtaining examination results of the suspected patients. Previous research stated that using radiologic images could be utilized to detect COVID-19 before the symptoms appeared. With the rapid development of Artificial intelligence in medical imaging in recent years, deep learning as the core of this technology could achieve human-level-performance in diagnostic accuracy. In this paper, deep learning was implemented to detect COVID-19 using a chest X-ray dataset. The proposed model employed a multi-kernel convolution neural network (CNN) block combined with pre-trained ResNet-34 to overcome an imbalanced dataset. The model block adopted different kernel sizes as follows 1x1, 3x3, 5x5, and 7x7. The findings show that the proposed model is capable of performing binary and three class classification tasks with an accuracy of 100% and 93.51% in the validation phase and 95% and 83% in the test phase, respectively.
Gender inequality among champions and players’ reception of gender disproportion of utility support champions in league of legends

Designing female character in video game has been criticized as being sexually objectified and underrepresented in quantity (number of characters and their appearance rate in the game) and in quality (take only secondary role and inferior ability statistics given). In this paper, we analyze world leading multiple-user online battle arena game league of legends to see if previously criticized gender inequality of champions still stands and conduct a survey of 1,403 players of that game and asks how they feel about serious gender disproportion of utility support champions (all females). The result shows that league of legends still has serious gender disparity in performance parameters and there has been only a small change in 5-year span (2014-2019). The survey result tells us that game players also feel political incorrectness of such gender disproportion, but they accept such gender prototype because they have been taught as such as social role theory explains gender inequality issues.