Miracle-dz/UniFAR-FTUs huggingface dataset:
Low-Cost Virtual Reality System ∗ PC-Driven VR system Technical

The concept of Virtual Reality has been around since early 1960s, but the availability and development of Virtual Reality systems were largely limited due to its nature of high cost and diﬃculty in maintenance. Until recently, thanks to the fast development of the modern technology, the idea of building Virtual Reality system using commodity-oﬀ-the-shelf hardware became feasible. By using Personal Computers, we have in this project developed a Low-Cost Distributed Virtual Reality system that is much cheaper, easier to maintain and mobile. In this project, the design of stereo vision, corner projection and distributed architecture had been discussed and applied in the implementation of the Virtual Reality system. User experiment had been conducted. The aim of the user experiment is to test the system for presence level, Slater, Usoh and Steed (SUS) questionnaire was used as an indication to the level of presence. Furthermore, network performance related to scene complexities were also evaluated. From these experiment, we have found that the Virtual Reality system developed creates a good level of presence to the participants and scene complexity would inﬂuence the roundtrip time of the network. Lastly, this paper concludes by discussing why the Low-Cost Virtual Reality system developed to be an eﬀective Virtual Reality system.
Molecular identification and phylogenetic analysis of Trypanosoma evansi in dromedaries (Camelus dromedarius) from Iran

Surra is of great concern to countries in the world such as Iran, which have a considerable camel population. The present study was aimed at determining the prevalence of Trypanosoma evansi in the camels of Iran. A total of 167 blood samples from farmed camels were examined for the presence of T. evansi infection using parasitological and molecular methods. Blood smear examination revealed 10 (6%) positive samples, while the PCR method 14 (8.4%) found positive samples. Age, sex, and region were not determined as risk factors for T. evansi infection in this study. The phylogenetic tree inferred from VSG gene sequences of T. evansi clearly separated the sequences of this study into two clades, A and B, which reflects the intrasequence heterogeneity among Iranian isolates. The phylogenetic tree showed that Iranian T. evansi strains are members of the T. brucei clade.
Trends and Determinants of Innovation in Asia-Pacific and Latin America and the Caribbean

We present a comparative analysis of innovation trends and determinants of innovation in the Asia-Pacific region versus the Latin America and the Caribbean region. We sift through several measures of innovation to map out the patterns of innovation in the two regions. The indicators include researcher density, research and development spending, patenting, high-technology exports, economic complexity index, scientific publications and trademark flows. Overall, the stylized facts clearly show that Asia-Pacific innovates more than Latin America and the Caribbean. At the same, there is considerable intra-regional heterogeneity and aggregate regional innovation is driven largely by higher-income countries. More formal empirical analysis based on panel regression techniques shows that investment in R&D, secondary school enrolment, and infrastructure access are the key drivers of innovation. However, these factors are conditional on the type of innovation and on the region.
A Morphometric Study of the Mandibular Foramen in Dry Adult Human Mandibles in a Black Malawian Population

The inferior alveolar nerve block(IANB) technique is a common technique performed on patients in dental surgery, placement of mandibular implants and other procedures involving the mandible. Precise identification of the mandibular foramen (MF) is essential for dental surgeons to accurately administer local anesthetics. Inaccurate localization of the mandibular foramen may result in IANB failure and injury to neurovascular tissues. Therefore, this study aimed at investigating the precise location of the MF from various anatomical land marks in dry adult human mandibles of Malawian population. The study was conducted on 29 dry adult human mandibles of unknown sex of Malawian origin from the Anatomy Division collection of human skeletons housed in the Biomedical Sciences Department, College of Medicine, University of Malawi. To determine the position of the mandibular foramen, distances from mandibular foramen to anterior margin, posterior margin, mandibular notch, gonial angle and mandibular base using a Vernier caliper were measured. The mean distance of the MF from posterior margin of mandibular ramus was 11.26± 1.22 mm (right side) and 11.47± 1.35 mm (left side), from the anterior margin 20.85± 3.12 mm (right side) and 20.85± 3.22 mm (left side) mandibles. The mean distance between mandibular notch (MN) and MF was 23.87± 2.61 mm (right side) and 23.53 ± 2.65 mm (left side). The mean distance between mandibular base(MB) and MF for the right and left were 28.47 ± 2.90 mm and 27.85 ± 2.99 mm respectively. The inferior limit of the mandibular foramen was located at 24.69 ± 3.65 mm (right side) and 24.25 ± 2.77 mm (left side) to the angle (AG) of the mandible. The findings of this study show that the anterior margin mean distance from the MF for both right and left mandibles seem to be bilateral symmetrical suggesting the interpretation that the needle for IANB could be inserted at about 21 mm from the anterior margin to the MF in an adult of Malawian origin during surgery.
Supplementary Material for “Combined Depth Space Based Architecture Search For Person Re-identiﬁcation”

Different from normal NAS, we aim to search for most suitable network architectures for ReID. Therefore, we directly search the network architectures on Market1501 [10]. In Market1501, the dataset is divided into a training set with 12936 images of 751 persons and a testing set of 750 persons containing 3368 query images and 19732 gallery images. According to the proposed Top-k Sample Search, we need to split the training set into a new training set and a validation set. For each identity, we select 4 images to construct the validation set. We utilize the triplet sampler as in [5] on both training set and validation set to prepare the batch data. Particularly, we choose the batch size as 64 and the number of identities per batch is 16, namely each identity has 4 instances per batch. SGD optimizer with weight decay 3e-4 and Adam optimizer with weight decay 0.001 are utilized for the network parameters and the architecture parameters optimization respectively. The network parameters learning rate ηw starts from 0.025 and decays to 0.0001 via a cosine lr scheduler while architecture parameters learning rate ηα starts from 3e-4 and decayed by 0.1 at 80, 160 epochs. Totally, we train the search network for 240 epochs. During the training process, softmax loss and triplet loss are jointly utilized for optimization and the margin of triplet loss is 0.3. In Tab. 1, we show the inner structures of CNet and CDNet via Top-k Sample Search, where k ∈ {1, 2, 3, 4}. As analyzed in main manuscript (section 4.1), the architectures searched via top-2 sample search almost achieve the best performance. As for CNet, the best architecture (top-2 CNet) tends to select large kernel combination thus makes up the defect of shallow depth. Note that the depth of CDNet can vary from 6 to 12 and none of the searched architectures choose the biggest depth. As we can see,
Evaluation of Antioxidant Ability In Vitro and Bioavailability of trans-Cinnamic Acid Nanoparticle by Liquid Antisolvent Precipitate

TCD is a kind of organic acid that is isolated from cinnamon bark or benzoin. TCD has significant antioxidant activity and is widely used in pharmaceutical, cosmetic, and food additives. But TCD has shortcomings of low bioavailability due to poor water solubility. Therefore, we use ethanol as a solvent, deionized water as antisolvent, and hydroxypropyl methylcellulose HPMC as the surfactant to prepare TCD nanoparticle powder. The optimum preparation conditions were determined as follows: TCD-ethanol solution concentration was 170 mg/mL, the volume ratio of antisolvent was 4 times that of solvent, and the amount of the surfactant was 0.3% stirred for 10 min by 2500 rpm; TCD nanoparticle with a mean particle size MPS of 130±12.5 nm is obtained under the optimum conditions. SEM, FT-IR, LC-MS/MS, XRD, and DSC were used to characterize the TCD nanoparticle. The results showed that the chemical structure of TCD nanoparticle was not changed, but the crystallization was significantly reduced. Solubility, dissolution rate, antioxidant activity, the in vitro transdermal penetration, and bioavailability of TCD nanoparticles were all much better than these of the raw TCD. These results suggested that TCD nanoparticle might have potential value to become a new oral or transdermal TCD formulation with high bioavailability.
A comparative analysis of trajectory similarity measures

ABSTRACT Computing trajectory similarity is a fundamental operation in movement analytics, required in search, clustering, and classification of trajectories, for example. Yet the range of different but interrelated trajectory similarity measures can be bewildering for researchers and practitioners alike. This paper describes a systematic comparison and methodical exploration of trajectory similarity measures. Specifically, this paper compares five of the most important and commonly used similarity measures: dynamic time warping (DTW), edit distance (EDR), longest common subsequence (LCSS), discrete Fréchet distance (DFD), and Fréchet distance (FD). The paper begins with a thorough conceptual and theoretical comparison. This comparison highlights the similarities and differences between measures in connection with six different characteristics, including their handling of a relative versus absolute time and space, tolerance to outliers, and computational efficiency. The paper further reports on an empirical evaluation of similarity in trajectories with contrasting properties: data about constrained bus movements in a transportation network, and the unconstrained movements of wading birds in a coastal environment. A set of four experiments: a. creates a measurement baseline by comparing similarity measures to a single trajectory subjected to various transformations; b. explores the behavior of similarity measures on network-constrained bus trajectories, grouped based on spatial and on temporal similarity; c. assesses similarity with respect to known behavioral annotations (flight and foraging of oystercatchers); and d. compares bird and bus activity to examine whether they are distinguishable based solely on their movement patterns. The results show that in all instances both the absolute value and the ordering of similarity may be sensitive to the choice of measure. In general, all measures were more able to distinguish spatial differences in trajectories than temporal differences. The paper concludes with a high-level summary of advice and recommendations for selecting and using trajectory similarity measures in practice, with conclusions spanning our three complementary perspectives: conceptual, theoretical, and empirical.
A Comparison of 25GHz-LC-VCO Circuit Topologies for SEU Mitigation in 22nm FinFET

Three LC-tank voltage-controlled oscillators (VCOs) are designed in a 22nm FinFET process with varactor and tail filter permutations to compare their sensitivity to single event upsets (SEUs) and understand the overhead these circuit techniques have on electrical performance. Each VCO has a tuning range from 15.8-25.9GHz yielding a tuning aware FOM of 186.12dBc/Hz for the radiation hardened VCO design. Furthermore, these three VCOs where tested at the Texas A&M Cyclotron Institute at linear energy transfer (LET) levels of 10, 35, and 70 MeV.cm2/mg. Testing results showed both a marked decrease in the VCO area sensitive to radiation when using the rad hard varactor tank configuration, and the effectiveness of the LC tail filter for both phase noise and SEU mitigation.
Image-text discourse coherence relation discoveries on multi-image and multi-text documents

The occurrences of the image-text pairs are common in social media such as image captions, image annotations, and cooking instructions. However, the links between images and texts as well as the coherence relationship among them are always implicit. We developed a multi-modal approach by firstly establishing the links between image and text in an unsupervised way, then discovered their coherence relations through computational models of discourse to improve the consistency and quality of the images and their corresponding texts and also explore a dynamic and flexible image-text coherence relation.
The use of Saccharomyces cerevisiae fermented coconut dregs with the addition of sodium selenite as a source of selenium in broiler diets

Fermentation has been practised in feed technology to bioconvert the inorganic minerals to organic compounds. A study was done to determine the effect of Saccharomyces cerevisiae fermented coconut dregs with the addition of selenium on growth performance, feed digestibility and the intestinal response of broiler chickens. The study used 112-day old unsexed broiler chicks for 6 weeks. The broilers were fed with 4 different experimental diets. The diets were basal diet (T1), basal diet plus 0.5% coconut dregs (T2), basal diet plus 0.5% of 5 days fermented coconut dregs (T3) and basal diet plus 0.5% of 7 days fermented coconut dregs (T4). The broilers were fed ad libitum and tap water was offered at all times. The broiler chicks were vaccinated against New Castle Diseases on the fourth day. Feeders and drinkers were placed inside the pen. The feeders, drinkers, pens and surroundings were cleaned whenever necessary. A completely randomized design was used in this study with four different treatment diets, four replicate cages of 7 birds each. The data found in this study was analyzed using an analysis of variance. A Tukey test was applied once a significant effect was detected in the analysis of variance. Results of the study indicate that body weight gain and dry matter digestibility increased when the birds were fed the diets T3 and T4. The relative gizzard weight of birds fed the T3 and T4 was lighter than the birds fed the T1 and T2. Feed intake, feed conversion ratio, carcass percentage and relative intestine weight were not affected by the experimental diets. In conclusion, feeding the birds with diets supplemented with Saccharomyces cerevisiae-fermented coconut dregs with additional selenium improved feed quality and broiler performance.
Deep learning and Its Development

Deep learning is a promising branch of machine learning. It is an algorithm that uses artificial neural networks as the architecture to characterize and learn data. In recent years, many companies, for example, Google, Microsoft and Baidu, have become interested in the field of deep learning and have set up many large-scale projects, such as Google’s Deepmind project, including alphago, which has achieved success in Go and e-sports. This article analyzes and summarizes each current research direction and approach of deep learning, with prospection about the future research direction and development of deep learning expounded. An overview of the three basic models of deep learning is given, namely multilayer perceptrons and perceptrons, convolutional neural networks and recurrent neural networks. The benefits and superiority of the deep learning algorithm are illustrated and compared with the conventional methodology used in the common applications. Further research on emerging types of convolutional neural networks and recurrent neural networks are introduced. An overview of the three basic models of deep learning is given, namely multilayer perceptrons and perceptrons, convolutional neural networks and recurrent neural networks. The current application of deep learning in various fields is summarized, such as artificial intelligence, computer vision and natural language processing applications, and some open problems for future research are also analyzed. Finally, the significance and purpose of deep learning are discussed.
The Vertical Profile of Chlorophyll-a in the Waters of Submarine Volcano of Kawio Barat, Indonesia

The submarine volcano can release various materials into the waters and affect the distribution of chlorophyll. Nevertheless, studies in such kinds of exciting areas are rarely done. This study aims to determine the vertical profile of chlorophyll-a around the submarine volcano waters. A field survey was conducted in October 2018 in the photic zone (200 m) around the Kawio Barat submarine volcano waters, North Sulawesi Province, Indonesia. Chlorophyll fluorescence was measured using a sensor of WET Labs ECO-AFL/FL as a proxy of chlorophyll-a. The temperature, salinity, and depth were measured using a CTD. The nutrients, including nitrate, orthophosphate, and silicate, were measured using autoanalyzer Skalar SAN++. The average of chlorophyll-a values ranged between 0.098 - 0.175 mg/m3. The highest average chlorophyll-a was found around the waters of Kawio Barat submarine-volcano. The vertical profile of chlorophyll-a indicated a forming of Deep Chlorophyll Maxima (DCM), located at a depth of 69 - 90 meters. In the Kawio Barat submarine volcano waters, the DCM is found in a depth of 90 m. It has chlorophyll-a concentration four times higher than the surface (5 m). The Principal of Component Analysis (PCA) shows that the temperature and salinity have a more substantial influence on the value of chlorophyll-a. Meanwhile, the nutrients are more influence firmly on the depth of DCM. This current study may conclude that the Kawio Barat submarine volcano waters are more productive than the other stations.
Grace: Interpretable Root Cause Analysis by Graph Convolutional Network for Microservices

With the development of cloud applications, large monolithic services have been replaced by loosely-coupled and single-purpose microservices. To improve localization performance, deep learning techniques have been widely used for root cause analysis. Existing research focuses on performance, yet the lack of interpretability creates key barriers to applying deep learning models in practice. This paper presents Grace, an interpretable root cause localization framework. Our work has three aims. First, to more accurately localize root causes using a Spatial-Temporal Graph Convolutional Network (STGCN). To the best of our knowledge, we are the first to apply an STGCN in the domain. Second, to design an interpreter that helps engineers to understand the system decision (beyond the simple binary black-box result). Third, we apply our interpreter to two real cases, which replaces expert knowledge to help build prior knowledge for fault type diagnosis. Our results show that Grace consistently achieves improvements over other state-of-the-art models by 4%-140%.
Effect of operating parameters and chemical treatment on the tribological performance of natural fiber composites: A review

ABSTRACT The demand for high-performance engineering products made from natural resources is increasing because of the low-cost, low-density, biodegradability, renewable nature and lighter than synthetic fibers. With these characteristics, the tribological performance of natural fiber composite has become an important element to be considered in most industrial and manufacturing functions. This paper presents an overview of the factors that influence the tribological performance of natural fiber composites, which include applied load, sliding distance, sliding velocity and fiber orientation. Influences of chemical treatment is also reviewed and illustrated through scanning electron microscope (SEM) observations. This review will focus on kenaf fibers (KFs) and oil palm fibers (OPFs) which have been widely exploited over the past few years among the available natural resources. The results show that the operating parameter, fiber orientation and chemical treatment has significant effects on the tribological performance of natural composite. A clear understanding of the factors that affect the tribological performance is very essential in performance improvement on natural fibers reinforced polymer composite for potential applications.
Anti-bacterial activity of Dayak onions extract (Eleutherine palmifolia) against Salmonella spp and Escherichia coli

Dayak onions (Eleutherine palmifolia) is a plant from Kalimantan. Dayak onions contain high flavonoid and phenol compounds and can be used as an alternative feed additive for broilers to replace synthetic antibiotics that can cause resistance and residues. This study aims to determine how much the ability of Dayak onions extract to inhibit Salmonella spp and Escherichia coli bacteria by using factorial randomized design and Duncan’s advanced test with three replications. The first factor was the maceration test consisting of control using tetracycline and replication of maceration I, maceration II, combined maceration I and II. The second factor is the concentration consisting of three concentrations of 0.50%, 1.00% and 1.50%. Antimicrobial activity is characterized by the presence of a clear zone that forms around a good hole. The results showed that the best antimicrobial activity of Dayak onion extract was obtained in K3M1 with inhibitory zone diameters of 15.47 mm for Salmonella spp and 13.40 mm for Escherichia coli. The value of the diameter of the inhibition zone shows a high sensitivity level as an antibacterial. The lowest diameter value of the inhibition zone was K1M2 which was 3.40 mm for Salmonella spp and 4.18 mm for Escherichia coli. It was concluded that the best replication factor of the antibacterial activity was at M1 and the higher the concentration of Dayak onion extract was used, the higher the antibacterial activity and could be used as an alternative feed additive.
Selection of beef cattle type characters in Bali young bull from smallholder farms through individual control for the purpose of artificial insemination

Some of the male Bali cattle kept at the Artificial Insemination Center are the result of selection from the weaning process to become bulls. Therefore, this study aimed to determine the extent bulls selected from smallholder farms have the same quality spermatozoa as the males raised by the Institute for Artificial Insemination. The research method began in 2016-2018, which selected the performance of 50 heads, followed by a selection of biological characters, ejaculation, and livestock health in young bulls. Selected bulls were trained to collect their sperm and the quality of their sperm was examined macroscopically and microscopically. The results showed that 15 young bulls were selected by performance selection and four bulls were selected for selection based on the quality of frozen semen. Three bulls passed the selection to meet the frozen semen requirements of the Indonesian National Standard. The conclusion of this study is that the provision of males to the Institute for Center of Artificial Insemination can be done by selecting the best bull belonging to the farm community.