Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Fabrication of a Novel Ultra Compact Microstrip Diplexer Using Interdigital and Spiral Cells

A dual-band bandpass-bandpass microstrip diplexer with very small size and good performance is designed in this work. The proposed diplexer has a novel structure which is introduced for the 1st time in this paper. In comparison with the previously reported diplexers, it occupies the most compact size of 0.002 λg2 (226.7 mm2), fabricated on 0.787 mm dielectric substrate height. The resonance frequencies of the presented diplexer are located at 0.76 GHz and 1.79 GHz making it suitable for the global system for mobile communications applications. It has a wide flat channels with two fractional bandwidths (FBWs) of 41.1% and 50%. Another feature of the proposed diplexer is its ability to suppress the harmonics. It can attenuate the 1st–7th harmonics. Moreover, it has low insertion losses and low group delays at both channels, whereas the isolation and return losses are acceptable. Finally, the proposed diplexer is fabricated and measured to verify the simulation results, where a good agreement between the simulation and measurement results is obtained.
Composite Bacterial Infection Index and Serum Amyloid A Protein in Pulmonary Tuberculosis Patients and their Household Contacts in Makassar

BACKGROUND: Early diagnosis of tuberculosis (TB) cases in limited resource remains challenging. It is urgent to identify the new diagnostic tools which can control the spread of disease with accurate and rapid test. AIM: This study aimed to investigate the levels of infection markers: Composite bacterial infection index (CBII) and serum amyloid A (SAA) protein in pulmonary TB (PTB), and their healthy household contacts, as the alternative diagnostic markers for TB. METHODS: CBII and SAA were measured from 44 new PTB patients, and 31 household contact serum samples. The value of CBII was calculated from neutrophils, lymphocytes, monocytes, erythrocyte sedimentation rate, and high-sensitivity C-reactive protein (hs-CRP) level. hs-CRP and SAA levels were quantified from their serum samples using ELISA. QuantiFERON-TB Gold Plus (interferon gamma release assay [IGRA]) was used to screen latent TB infection among household contacts. RESULTS: Among 31 household contacts, there were 24 positive IGRA results and the rest (n = 7) had negative results. PTB patients exhibited significantly higher level CBII in the serum specimens, than those in household contact (p < 0.0001). There was no significant difference in the SAA level between TB cases and household contacts (p = 0.679). CONCLUSIONS: CBII can be used as one of the biomarkers for the identification of PTB from the serum specimens. Edited by: Ksenija Bogoeva-Kostovska Citation: Handayani I, Massi MN, Leman Y, Natzir R, Patellongi I, Subair S, Hidayah N, Wulandari AA, Halik H. Composite Bacterial Infection Index and Serum Amyloid A Protein in Pulmonary Tuberculosis Patients and their Household Contacts in Makassar. Open Access Maced J Med Sci. 2021 Jun 10; 9(B):557-562. https://doi.org/10.3889/oamjms.2021. 6114
AUTOMATIC SEGMENTATION OF POINT CLOUDS IN THE ARCHITECTURE ENVIRONMENT

Abstract. Correct and reliable identification and classification of different structures and infrastructures that make up a city (e.g. residential buildings, school buildings, hospitals, power stations, routes of communication, etc.) are of great importance for the AEC/FM (Architecture, Engineering, Construction, and Facilities Management) domain and for seismic risk assessments, among others. For decades, the method of collecting buildings information has been through field campaigns. This practice requires significant resources in terms of qualified engineers or architects to identify the geometry of the different elements that constitute the structure, building materials and construction processes. Nowadays, there are different geospatial techniques that allow data acquisition on a massive scale in a short period of time. In particular, by means of laser measurements, it is possible to have clouds of millions of points with geometric and radiometric information in a matter of seconds. In this article, we present ABM-indoor, a LIDAR-based approach that automatically provides a three-dimensional models of buildings in vector format. Models include floors, ceilings, walls (up to five dominant directions), columns, elements located on floors and elements hanging from ceilings. Efforts are underway to transfer this model to a Building Information Model (BIM).
Attitudes Towards Utilising Mobile Banking Applications Among Generation Z Consumers in South Africa

In today’s post-modern era, the banking industry is becoming a digital rather than a physical system. Digital banking has been synonymous with the fourth industrial revolution making a notable impact on the African continent. Therefore, the purpose of this research is to empirically investigate consumer attitudes towards mobile banking applications in South Africa. A positivist paradigm underpinned the study, and a descriptive design was employed. To test the proposed hypotheses a unique conceptual model was developed. Non-probability sampling was adopted in selecting appropriate participants. Data was collected from 325 willing participants through a survey. In terms of analysis, SPSS and AMOS were utilised to generate descriptive statistics and hypotheses testing. The results established that attitudes towards mobile banking applications and actual use of mobile banking applications was the strongest relationship. The empirical evidence presented in this study adds value to the existing research on mobile-banking within the 4th industrial revolution, particularly in South Africa, a largely underresearched area. ISSN: 2723-1097
APPROACHES FOR SOFTWARE PERFORMANCE FEEDBACK

— Over the last decade, research has highlighted the importance of integrating the performance analysis in the software development process. Software Performance Engineering (SPE) has been recognized as the discipline that represents the entire collection of engineering activities, used throughout the software development cycle, and directed to meet performance requirements. Performance is in fact an essential quality attribute of every software system; it is a complex and a pervasive property difficult to understand. If performance targets are not met, a variety of negative consequences (such as damaged customer relations, business failures, lost income, etc.) can impact on a significant fraction of projects. Performance problems cause delays, failures on deployment, redesigns, even a new implementation of the system or abandonment of projects, which lead to significant costs. All these factors motivate the activities of modeling and analyzing the performance of software systems at the earlier phases of the lifecycle by reasoning on predictive quantitative. To provide an automated feedback to make the performance analysis results usable at the software architectural level. Results in order to avoid an expensive rework, possibly involving the overall software system.
RLSNAKE: A HYBRID REINFORCEMENT LEARNING APPROACH FOR ROAD DETECTION

Abstract. Road network detection from very high resolution satellite and aerial images is highly important for diverse domains. Although an expert can label road pixels in a given image, this operation is prone to error and quite time consuming remembering that road maps must be updated regularly. Therefore, various computer vision based automated algorithms have been proposed in the last two decades. Nevertheless, due to the diversity of scenes, the field is still open for robust methods which might detect roads on different resolution images of different type of environments. In this study, we picked an earlier proposed road detection method which works based on traditional computer vision and probability theory algorithms. We improved it by further steps using reinforcement learning theory. With the help of the novel hybrid technique (traditional computer vision method combined with reinforcement learning based artificial intelligence), we achieved a solution that we call RLSnake. This new method can learn new image scenes and resolutions rapidly and can work reliably. We believe that the proposed RLSnake will be a significant step in the remote sensing field in order to develop solutions which might increase performance by combining the power of traditional and new techniques.
Effect of L-Arginine Supplementation in Ossimi Rams’ Diets on Biometry of Testes and Epididymis, Immune-Histochemical Expression and Characteristics of Epididymal Spermatozoa

This experiment was conducted to evaluate the impact of dietary L-arginine supplementation on some epididymal spermatozoa characteristics, differential White blood cells count, some reproductive organs'metrics. Fifteen adult Ossimi rams averaging 44.9± 0.57 kg were utilized, divided into three comparable groups (5 rams each) , were fed a basal ration supplemented with Larginine at concentration of 0.0 (G1) or 0.5(G2) or 1.0%(G3) of body weight/day for two months. At the end of the study rams were slaughtered for conducting biometric studies on tests and epididymis and testicular Immunohistochemical NOS analysis. Epididymis Semen was collected and evaluated for motility, viability, abnormality and acrosome integrity.L-arginine Supplementation at 0.5(G2) or 1.0%(G3) significantly (P<0.05) improved epididymal spermatozoa characteristics, as % of motility, livability, acrosome integrity while, % of dead and abnormal spermatozoa decreased in supplemented groups as compared with G1. This improving was greatest in G2 than that happened in G3. Measurements of testes and epididymis increased in G2 and G3 compared with G1 . In addition, there was a significant increase of immunoexpression of testicular Nitric oxide synthase (NOS) in rams received L-arginine at 1% or 0.5% of body weight/day as compared to G1, and this expression was clearly found within the spermatid layer and few sertoli cells in both treated groups, while in G1, it was limited to spermatid layer only. It could be concluded that dietary Larginine supplementation to Ossimi ram ration has positive effects on epididymal spermatozoa characteristics, Sexual organs anthropometries and immunohistochemical expression of testicular NOS.
Implementation of Electronic Medical Records for Service Delivery in Selected State Hospitals in Southwest Nigeria

Electronic Medical Records (EMR) is an important communications channel relating to patient health conditions. Unfortunately, many hospitals in Africa, including Nigeria, have not implemented EMR. The few Hospitals that have some level of EMR continues are still struggling with the use of paper and hybrid medical records, which has led to inadequate medical follow-up, medical error, and long waiting time for patients. A sample size of three hundred and ninety-seven (397) was determined using krejcie and morgan models, comprising of strategic managers, and the operational staff drawn from a population of 2889 in the selected hospitals. At the hospital level, purposive sampling was applied in picking strategic managers, while stratified random sampling was method was used to select operational health workers. Questionnaires were used for data collection. The study adopted a descriptive statistical analysis method to describe the existing medical records systems. The finding indicated that the systems in the hospitals are mainly paper-based. The hospitals are also using hybrid system with a few treatment areas having fully electronic medical records systems. In the area where EMR has been implemented, the finding indicates poor penetration of the EMR system, limited modules, staff readiness and poor performance in the treatment area, among others. The study concluded that hospitals that have implemented, EMR is not serving the classical purpose of medical record of supporting treatment and follow up. The study recommended that the selected hospitals should ensure there is the availability of fund, staff training, and technical infrastructures like electronic record managers, ICT support staff, and computer compatible medical devices, among others.
Stress, psychosocial factors and the New Zealand forest industry workforce: Seeing past the risk of harm to the potential for individual and organisational wellbeing

Background: There is clear evidence that stress is having an impact on the health and wellbeing of the forest industry workforce in Aotearoa New Zealand. While this has legal ramifications under the national health and safety legislation, international research also shows that harm to mental health invariably leads to reductions in work force productivity and business profitability. The reverse is also true: improved mental wellbeing can lead to greater worker engagement and commitment, which in turn increases productivity and profitability. Although these relationships are well substantiated, managers and leaders in the forest industry may not be aware of either the existence of a workplace stress problem or of its impact. Methods: A critical review is undertaken of stress and psychosocial hazards research within the international forest industry or similar industries (e.g. construction), with particular attention given to the explanation of psychosocial hazards. Results: International research on the forest industry largely confirms what we know about harmful aspects of job content and workplace conditions. However, it is argued that the focus within this research on job content and immediate workplace conditions obscures the impact of the wider social context. This limits the potential of management to move beyond seeing psychosocial factors simply as risks to be minimised at the workplace level. Bringing an ecological perspective to the analysis of forestry workplaces makes it easier to identify the elements of forest management practice that may contribute to stress within the workforce. It also becomes easier to identify the interactions between family, community and workplaces that may either exacerbate or reduce workforce stress. Conclusions: This paper highlights particular opportunities for reducing stress and enhancing wellbeing within the New Zealand forest industry workforce. It suggests that the psychosocial conditions that contribute to mental ill-health can be reconfigured to promote mental health, with wellbeing benefits that extend beyond the workplace. Psychosocial demands on a person can be motivating as long as the person has the resources to meet the challenge. Successful stewardship of the psychosocial environment at the forest management level is thus an opportunity to increase value to both investors and other stakeholders. New Zealand Journal of Forestry Science Best et al. New Zealand Journal of Forestry Science (2021) 51:5 https://doi.org/10.33494/nzjfs512021x93x
Molecular identification of arbuscular mycorrhizal fungal spores associated to the rhizosphere of Retama raetam in Tunisia

ABSTRACT Arbuscular mycorrhizal fungi (AMF) are found in the soil of most ecosystems where they form mutualistic associations that affect plants growth. We have investigated the community structure of AMF associated to Retama raetam growing in five regions of Tunisia. The total number of spores was significantly different across sites, ranging from 633 to 1062 spores per 100 g dry soil. A dominance of small spores was revealed. The large subunit region of the rDNA of AMF spores associated to the rhizosphere of R. raetam was sequenced. Sequences clustered into 13 operational taxonomic units. Phylogenetic analysis revealed that the majority of sequences were grouped within Glomeraceae and Claroideoglomeraceae families. Only two sequences were affiliated to the Scutellospora genus. These results suggest the dominance of the genus Glomus in the soil rhizosphere of R. raetam. A correlation between phylogenetic analysis, soil chemicals properties, and AMF community richness was also detected.
Matera: the Sassi through Trade, Consumption and Tourism

Th e European Capital of Culture (ECoC) process-event has contributed to amplify the main transformations of the commercial structure in Matera. Th is paper proposes an analysis of the recent transformation of the historical Sassi neighborhood, aimed at pointing out the changes in trade and consumption practices, considering the eff ects that the development of tourism, one among the main drivers of the changes occurred, has produced in this area. Indeed, the Sassi neighborhood represents a defi nitely peculiar commercial and touristic landscape: from the year of designation of Matera as ECoC until today, the neighborhood – already a privileged destination for local tourism – has invested in a decisive reconversion of its commercial spaces, focused on the food & drink segment. Th ese commercial activities are addressed mainly for tourists, therefore the fi rst and most evident result is, actually, the exclusion of the residents. What are the characteristics of such a touristic change? What is the position of these places in the urban context? What are the functions that characterize them? Attempting to answer these questions will enable to highlight the specifi c characteristics of the Sassi and their development based on the most remarkable forms of touristifi cation.
IMAGE TO POINT CLOUD TRANSLATION USING CONDITIONAL GENERATIVE ADVERSARIAL NETWORK FOR AIRBORNE LIDAR DATA

This study introduces a novel image to a 3D point-cloud translation method with a conditional generative adversarial network that creates a large-scale 3D point cloud. This can generate supervised point clouds observed via airborne LiDAR from aerial images. The network is composed of an encoder to produce latent features of input images, generator to translate latent features to fake point clouds, and discriminator to classify false or real point clouds. The encoder is a pre-trained ResNet; to overcome the difficulty of generating 3D point clouds in an outdoor scene, we use a FoldingNet with features from ResNet. After a fixed number of iterations, our generator can produce fake point clouds that correspond to the input image. Experimental results show that our network can learn and generate certain point clouds using the data from the 2018 IEEE GRSS Data Fusion Contest.
Influence of Particle Size Distribution on the Physical Characteristics of Pore-Filling Hydrate-Bearing Sediment

Nature gas hydrates (NGHs) are regarded as a potential alternative energy source due to their huge reserves and wide distribution. According to the geophysical surveys, the pore-filling hydrates occupy a large proportion of the global hydrate reserves, especially for the marine regions. Therefore, with a novel pore-scale 3D morphological modeling algorithm, this study systematically studied the effect of the particle size on the physical characteristics of the pore-filling hydrate-bearing sediment (HBS). The pore system evaluations and permeability simulations were performed by utilizing pore network modeling (PNM), and the thermal and electrical simulations were conducted by utilizing a finite volume method (FVM). The results show that for the HBS with smaller particle size, the average radius of the pores and throats would also be reduced, and the fractal dimension of the pore system would be increased. In addition, with the increasing hydrate saturation, the fractal dimension of the pore system will increase firstly and then decrease. And these parameter evolutions could impact the physical properties correspondingly; specifically, the decreasing particle size in the HBS would reduce the permeability and electrical conductivity of HBS and enhance the apparent thermal conductivity of HBS.
Birds Sound Classification Based on Machine Learning Algorithms

The bird classifier is a system that is equipped with an area machine learning technology and uses a machine learning method to store and classify bird calls. Bird species can be known by recording only the sound of the bird, which will make it easier for the system to manage. The system also provides species classification resources to allow automated species detection from observations that can teach a machine how to recognize whether or classify the species. Non-undesirable noises are filtered out of and sorted into data sets, where each sound is run via a noise suppression filter and a separate classification procedure so that the most useful data set can be easily processed. Mel-frequency cepstral coefficient (MFCC) is used and tested through different algorithms, namely Naïve Bayes, J4.8 and Multilayer perceptron (MLP), to classify bird species. J4.8 has the highest accuracy (78.40%) and is the best. Accuracy and elapsed time are (39.4 seconds).
INCREMENTAL MAP REFINEMENT OF BUILDING INFORMATION USING LIDAR POINT CLOUDS

Abstract. For autonomous systems, an accurate and precise map of the environment is of importance. Mapping from LiDAR point clouds is one of the promising ways to generate 3D environment models. However, there are many problems caused by inaccurate data, missing areas, low density of points and sensor noise. Also, it is often not possible or accurate enough to generate a map from only one measurement campaign. In this paper, we propose a method to incrementally refine the map by several measurements from different campaigns and represent the map in a hierarchical way with a measure indicating uncertainty and the level of detail for objects. The idea is thus to store all captured information with a tentative semantics and uncertainty – even when it is not yet complete. Hence, occulated areas are presented as well, which can be possibly improved by the supplemental observation from the next measurement campaign. The proposed 3D environment model framework and the incremental update method are evaluated using LiDAR scans obtained from Riegl Mobile Mapping System.
EARTHQUAKE PREDICTION EVALUATION BASED ON VLF DATA USING A NOVEL INTERSECTION-UNION METHOD

Electromagnetic phenomena, especially those in the Very Low Frequency/Low Frequency (VLF/LF) bands are promising for shortterm earthquake prediction. Seismo-ionospheric perturbations cause a variety of changes in different receiver-transmitter VLF/LF signal paths. Therefore, independent and simultaneous observations at different points thus in different VLF/LF signal propagation paths are necessary to better predict the earthquake. Most of the previous research on VLF data have been based on one path or limited number of paths which examined perturbations in the time domain and less attention has been paid to estimate the location of the earthquake. In the present research, using wavelet analysis, the temporal variations of seismo-ionospheric perturbations and the approximate time of earthquake are predicted. Clear disturbances are observed two weeks before the Kumamoto earthquake happened in Japan in 2016. The novelty of this study is to present an approach called Intersection-Union method to predict earthquake location. Based on the geometry of a VLF/LF network, the Intersection-Union method was introduced to estimate the earthquake epicenter. This method is based on the overlay of earthquake occurrence probable areas. With simultaneous use of different propagation paths by the Intersection-Union method, an area with a radius of about 300 km was determined as the probable location of the earthquake epicenter. The accuracy of the proposed method is 300 km compared with 1000 km accuracy of other earthquake location prediction scenarios. 1 *Corresponding author