Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Accessibility and Usability of Higher Education Institutions’ Websites of Jordan

Recently, various websites have become a popular means of deriving information. However, users still find it difficult to access the relevant data or use the websites. Hence, they require websites which offer accessible information and easy navigation. In this study, the researchers have investigated the accessibility of the different websites of the Jordanian universities. The researchers determined the accessibility of 30 websites and verified their compliance with the Guidelines 2.0 (WCAG 2.0) for accessing the web content, according to the World Wide Web Consortium (W3C). They tested the usability of the Al-Zaytoonah University website as a test study, by interviewing 6 students belonging to the University. They were asked to identify the pages directly, without any assistance or direction, and they were asked to describe the selection processes and assistive techniques that they used. The data was collected from these students for conducting the website usability test. 14 tasks were implemented in this study, like accessing their University webpages, e.g., homepages of the site and access to the e-learning sites from the university homepage. The time required for every task was assessed. Based on this study, the researchers could identify the websites that were error-free. The results indicated that most of the websites were not easily accessible and were difficult to use. Furthermore, when the researchers carried out the test study with the students, their results indicated that the user interface for every webpage needs improvement, rearrangement of the sequence of web links and addition of more tags and information.
Actor-Critic Deep Reinforcement Learning for Solving Job Shop Scheduling Problems

In the past decades, many optimization methods have been devised and applied to job shop scheduling problem (JSSP) to find the optimal solution. Many methods assumed that the scheduling results were applied to static environments, but the whole environments in the real world are always dynamic. Moreover, many unexpected events such as machine breakdowns and material problems may be present to adversely affect the initial job scheduling. This work views JSSP as a sequential decision making problem and proposes to use deep reinforcement learning to cope with this problem. The combination of deep learning and reinforcement learning avoids handcraft features as used in traditional reinforcement learning, and it is expected that the combination will make the whole learning phase more efficient. Our proposed model comprises actor network and critic network, both including convolution layers and fully connected layer. Actor network agent learns how to behave in different situations, while critic network helps agent evaluate the value of statement then return to actor network. This work proposes a parallel training method, combining asynchronous update as well as deep deterministic policy gradient (DDPG), to train the model. The whole network is trained with parallel training on a multi-agent environment and different simple dispatching rules are considered as actions. We evaluate our proposed model on more than ten instances that are present in a famous benchmark problem library – OR library. The evaluation results indicate that our method is comparative in static JSSP benchmark problems, and achieves a good balance between makespan and execution time in dynamic environments. Scheduling score of our method is 91.12% in static JSSP benchmark problems, and 80.78% in dynamic environments.
Perasan Daun Mengkudu (Morinda Citrifolia) Menghambat Pertumbuhan Bakteri Escherichia Coli Secara In Vitro

Daun mengkudu (Morinda citrifolia) mengandung senyawa kimia seperti : antrakuinon, alkaloid, saponin, flavanoid, dan terpenoid yang berperan sebagai antibakteri. Penelitian ini bertujuan untuk mengetahui kemampuan daun mengkudu (M. citrifolia) dalam menghambat pertumbuhan bakteri Escherihia coli (E. coli) secara in vitro. Penelitian ini menggunakan isolat bakteri E. coli ATCC 25922 yang diperoleh dari Laboratorium Mikrobiologi Fakultas Kedokteran, Universitas Udayana. Kemampuan perasan daun mengkudu untuk menghambat pertumbuhan bakteri E. coli ATCC 25922 diuji dengan uji hambatan metode Kirby-Bauer yang dimodifikasi. Rancangan penelitian yang digunakan adalah rancangan RAL (Rancangan Acak Lengkap) dengan lima perlakuan, satu kontrol positif dan empat kali ulangan. Hasil perasan daun mengkudu berasal dari 300 gram daun mengkudu yang dihaluskan kemudian diperas. Konsentrasi perasan daun mengkudu yang digunakan adalah 0%, 25%, 50%, 75%, 100% dan kontrol positif oxitetrasiklin. Semua data dianalisis secara statistik dengan SPSS 13 (Sampurna, 2008). Hasil penelitian menunjukkan bahwa perasan daun mengkudu secara signifikan mampu menghambat pertumbuhan bakteri E. coli (P<0,01). Rataan zona hambat yang terbentuk pada konsentrasi 0%, 25%, 50%, 75%, 100% secara berurutan adalah 0,00 mm 7,3 mm, 8,5 mm, 10,4 mm, 12,5 mm dan secara statistik sangat berbeda nyata. Ada kecenderungan semakin tinggi konsentrasi perasan daun mengkudu maka zona hambat yang terbentuk semakin besar dengan uji regresi yang di dapat Y = 0.091 + 0.411K - 0.006K2 + 0.00003320K3 dan r = 0,995.
A Novel Homeostasis Method to Improve the Learning Efficiency of Spiking Neural Networks

Spiking neural networks (SNNs) trained by spike timing dependent plasticity (STDP) is a promising computing paradigm for unsupervised artificial intelligence systems. During the learning procedure of SNNs trained by STDP, homeostasis method is always implemented to mitigate the inhomogeneity induced by inputs and initial synapse weights. If homeostasis is not achieved effectively, the learning efficiency will be affected due to unbalanced training of neurons in the same layer. In this paper, we propose a novel homeostasis method and carry out software simulations to evaluate the learning efficiency and performance of the proposed method compared with two classical SNN learning algorithms. Simulation results on the task of digital recognition of MNIST dataset show that, our proposed method can achieve a ~2 times higher learning efficiency while maintaining comparable performance.
Long Short-Term Memory (LSTM) Neural Networks Applied to Energy Disaggregation

Energy disaggregation is an estimation of appliance energy usage from a single meter without the needs of sub-metering. In this paper, three models of the neural networks, Decision Tree (DT), Deep Neural Networks (DNN), and Long Short-Term Memory (LSTM) were compared and implemented for energy disaggregation. The Reference Energy Disaggregation data set (REDD) dataset was used for training and testing the effectiveness of the models. It was found that the LSTM performed better performances in MAE, RMSE, and R-Square than that of the DT and the DNN networks by at least 37.38% and 86.26% respectively.
Comparison of Recurrent Neural Network Architectures for Wildfire Spread Modelling

Wildfire modelling is an attempt to reproduce fire behaviour. Through active fire analysis, it is possible to reproduce a dynamical process, such as wildfires, with limited duration time series data. Recurrent neural networks (RNNs) can model dynamic temporal behaviour due to their ability to remember their internal input. In this paper, we compare the Gated Recurrent Unit (GRU) and the Long Short-Term Memory (LSTM) network. We try to determine whether a wildfire continues to burn and given that it does, we aim to predict which one of the 8 cardinal directions the wildfire will spread in. Overall the GRU performs better for longer time series than the LSTM. We have shown that although we are reasonable at predicting the direction in which the wildfire will spread, we are not able to asses if the wildfire continues to burn due to the lack of auxiliary data.
Development of Rhythm-based and Morphology-based Algorithm for Atrial Fibrillation Detection From Single Lead ECG Signal

Atrial Fibrillation or AF is the most common atrial arrhythmia and often occurs especially in the elderly people. Since AF is associated with an increased risk for stroke, regular AF monitoring is recommended for the elderly as well as the patients to reduce the incidence of stroke. In this study, the subsequent two methods of AF detection have been. The first one is a low complexity algorithm with rhythm-based for embedding into portable ECG devices. The second one is morphology-based method using a transferred deep learning with fine-tuning. The performances of the low complexity algorithm are 100% of sensitivity and 86.67% of specificity, respectively while the performances of the deep learning algorithm are 96.97% of sensitivity and 100% of specificity, respectively. From these results, the combination between rhythm-based and morphology-based algorithm can offer the highest sensitivity for screening of AF and highest specificity for separating Normal Sinus Rhythm (NSR) from AF. These developed methods will be useful for improving the performance of AF detection utilized in healthcare system.
IXODID TICKS (ACARINA, IXODIDAE) OF CENTRAL AFRICA. VOLUME I. GENERAL INTRODUCTION. GENUS AMBLOYOMMA KOCH, 1844,

Abstract : The study consists of three parallel investigations: (1) survey and critical review of the world-wide literature dealing with the ixodid ticks of Central Africa in general and of the Congo, Rwanda and Burundi in particular; (2) examination and identification of available ixodid tick materials previously collected in Central Africa (Congo, Rwanda and Burundi), comprising some 70,000 specimens; and (3) collection and identification of new materials coupled with field and laboratory observations on the biology and ecology of some of the tick species occurring in the Kivu Province of the Congo and in the Republic of Rwanda. Up to the present time, 78 species of ixodid ticks belonging to nine genera have been reported from Central Africa (Congo, Rwanda and Burundi). Of this, the presence of 75 species in this area is validated by available materials and new collections. The geographical distribution, as well as the list of affected hosts vary with each species. Most of these species occur on a variety of domestic and wild animals and are capable of causing severe economic losses to the livestock industry as well as transmitting agents of human diseases. The results of these studies are presented in such a way that each genus is treated as a discrete unit in which each species is dealt with from the viewpoint of taxonomy, distribution and hosts, biology, relationship to disease, diagnosis, description and illustration. The distribution of each of the species in the Congo, Rwanda and Burundi is plotted individually on maps, and keys to the identification of the adults of each species are presented in the treatment of each genus. (Author)
DEVELOPMENT OF STANDARD PROTOCOLS FOR PREPARATION AND EVALUATION OF LIVER HOMOGENATE VACCINES AGAINST HYDROPERICARDIUM SYNDROME VIRUS IN POULTRY

Twelve different vaccines were prepared from hydropericardium syndrome (HPS) infected liver homogenate by using two different virus concentrations (1x10 2 and 1x10 3 ALD50) and two virus inactivants (0.1% formalin and 0.01% binary ethyleneimine) with and with out different adjuvants. These vaccines were evaluated in 13 groups of broilers (8 in each group) for their comparative immunogenicity and protection. At day 14 of age, chicks of groups A1, B1, C1 and D1 were vaccinated with 4 oil based vaccines (OB-HPSV) with two different virus concentrations (1x10 2 & 1x10 3 ALD50) and two different inactivants (0.1% formalin and 0.01% binary ethyleneimine), respectively. Chicks of groups A2, B2, C2 and D2 were vaccinated with 4 aluminized vaccines (AH-HPSV) using two virus concentrations and two inactivants. Similarly, chicks of groups A3, B3, C3 and D3 were vaccinated with non adjuvanted vaccines (NA-HPSV) with two virus concentrations and two inactivants. Group E was kept as unvaccinated control. All the vaccinated birds were found sero-positive 7 days post vaccination (PV). IHA GMT results indicated no difference for different virus concentrations and different virus inactivants with same adjuvant (P>0.05). The IHA GMT recorded weekly during 0-28 days PV was the highest and more consistent (52-181) for OB-HPSV, followed by AH-HPSV (52-147) and NA-HPSV (73.3-104). The protection recorded for OBHPSV vaccine was 100%, for AH-HPSV vaccine it 87.5% and with NA-HPSV vaccine it was 62.5% when challenged at 21 days post vaccination (PV). It was concluded that 1x10 2 ALD50 oil based vaccines inactivated with either formalin or binary ethyleneimine can be recommended for commercial use.
Freshness of Food Detection using IoT and Machine Learning

In today’s world, food spoilage is a crucial problem as consuming spoiled food is harmful for consumers. Our project aims at detecting spoiled food using appropriate sensors and monitoring gases released by the particular food item. A micro controller that senses this, issues an alert using internet of things, so that appropriate action can be taken. This has widescale application in food industries where food detection is done manually. We plan on implementing machine learning to this model so we can estimate how likely a food is going to get spoiled and in what duration, if brought from a particular vendor. This will increase competition among retailers to sell more healthy and fresh food and create a safe world for all consumers alike.
Features of Capacity of Communication Channel with APSK-N signals, which Implements the Theory of Resolution Time

The paper analyzes the features that arise in the process of information transmition using a multi-position amplitude-phase-shift signal with $N$ discrete states through a nonparametric, frequency-selective communication channel with intersymbol interference. We consider a class of channels utilizing the theory of resolution time. The greatest attention is paid to a study of properties of “transparency windows” in the presence of adverse factors such as frequency detuning and envelope and phase measurement errors introduced by the receiving device. Due to the obtained results recommendations are made to increase the speed in such communication channels.
A Framework for Evaluating Reintroduction Success in Carnivores: Lessons from African Wild Dogs

Summary To provide a framework for assessing reintroduction success in carnivores, I evaluated one of the most extensive endangered species reintroduction efforts to date, namely the establishment of an actively managed metapopulation of African wild dogs, Lycaon pictus, in South Africa. This intensive management approach involves the reintroduction of wild dogs into suitable conservation areas and periodic translocations among them. Analyses of individual survival, breeding success and population viability suggested that the crucial factor infl uencing wild dog reintroduction success is dispersal behaviour (natural or artifi cial) and the resulting formation (natural or artifi cial) of new packs, given the dependency of wild dogs to living in cohesive social groups for successful reproduction. This case study provides several lessons for reintroduction biologists. (1) It illustrates the virtue of defi ning criteria with which to gauge reintroduction success. (2) It outlines two potential modelling approaches for assessing short- and long-term reintroduction success. (3) It highlights how reintroduction success may be related to unanticipated factors. (4) It proposes future avenues for investigation specifi cally targeted
Dielectric and Thermal Behavior of PTFE/Sr2TiMnO6 (STMO) Composites

Development of materials with high dielectric permittivity is very much important for the miniaturization of electronic devices. From that perspective, polytetrafluoroethylene (PTFE) composites with up to 15 weight% Sr2TiMnO6 (STMO) ceramics were prepared using hot isostatic pressing method and characterized for their dielectric and thermal behavior. X-ray diffraction patterns showed the appearance of peaks corresponding to both PTFE and STMO in their composites, however, the intensities of the peaks were dependent on the loading of STMO. Thermal stability of the composites was superior to that of pure PTFE. Enhancement in the dielectric properties of PTFE was obtained from the addition of STMO. These composites with high permittivity can be explored further for their possible use in capacitor applications.
Deep Learning Based Resource Allocation in NOMA Wireless Power Transfer Networks

This paper investigates resource allocation of simultaneous wireless information and power transfer (SWIPT) in non-orthogonal multiple access (NOMA) system with power splitting (PS) technology. Our goal is to optimize both the harvested energy and the transmission rate subject to the minimum requirements on each user’s harvested energy and transmission rate. Considering the battery is capable of storing power which is converted into throughput in reverse link, we establish the equivalent-sum-rate (ESR) maximazation function by combining the transformed throughput and the transmission rate with a weight coefficient. Since the formulated nonconvex problem is difficult to solve, we develop a deep learning-based approach to obtain an efficient resource allocation strategy. In particular, deep belief network (DBN), which comprises preparing data samples, training and running, has been adopted. The simulation results verify the effectiveness of the proposed DBN-based scheme, and prove that the ESR performance of the considered NOMA-SWIPT is better than that of the OFDMA-SWIPT.
Etude des facteurs de la stérilité du bananier (Musa spp.) et des relations cytotaxinomiques entre M. acuminata COLLA et M. balbisiana COLLA

Deux especes participent a la constitution genetique des bananiers comestibles Musa acuminata COLLA et M balbisiana COLLA (2n = 22). La determination cytophotometrique des teneurs en ADN nucleaire de 3 clones appartenant aux 2 especes precedentes n'a pas mis en evidence de difference inter ou intra-specifique. La masse d'ADN est de 2,7 pg par noyau 2C. Les associations chromosomiques en meiose sont bonnes entre les 2 especes aux niveaux 2n, 3n et 4n. Actuellement, aucune difference significative ne peut etre mise en evidence entre les 2 genomes. Des remaniements chromosomiques reduisent la fertilite. Ils peuvent resulter de l'hybridation entre individus appartenant a des zones de diversification differentes. Une correlation significative existe entre le taux de tetrades spheriques et la fertilite pollinique, ce qui conduirait a donner une signification particuliere a l'orientation des 2 mitoses homeotypiques de la diade. La sterilite femelle d'origine chromosomique Des clones parthenocarpiques est accrue par une sterilite genique resultant de deviations de la formation des sacs embryonnaires, de la suppression de la fecondation et de l'avortement precoce des graines (relations d'incompatibilite entre l'embryon et l'albumen) Les tetraploides seminiferes obtenus par traitement de plantules a la colchicine ont montre un ralentissement de la croissance et une reduction du nombre de fleurs femelles et de la fertilite femelle. 3 quadrivalents potentiels sont formes par cellule en meiose. La fertilite mâle des 4n est bonne avec une distinction morphologique des gametophytes nette t 2n. L'importance du role des clones seminiferes dans le programme d'amelioration du bananier est discutee.
Allergen-Binding Activity of γE, γG and γA Antibodies in Sera from Atopic Patients

The antibodies associated with γG-, γA-, γM- and γE-globulins in the sera of ragweed sensitive patients were titrated by radioimmunodiffusion using I131-labeled antigen E and rabbit antibodies specific for each of these immunoglobulins. Quantitative measurements of the allergen-binding activities of the γG, γA and γE antibodies in the specimens were made by precipitation of the radioactive allergen-antibody complexes with rabbit antibodies. The titer of the antibodies in the radioimmunodiffusion method paralleled their allergen-binding activities. The skin-sensitizing activity of the patients' sera, which was determined by Prausnitz-Küstner reactions with antigen E, correlated with the allergen-binding activity of γE antibody but not with that of γG or γA antibodies. γM antibody was not detected in most of the samples containing high reaginic activity. Precipitation of γE-globulin removed the skin-sensitizing activity of the sera. These findings support the hypothesis that the reaginic antibody is associated with γE-globulin. The minimum dose of the skin-sensitizing antibody required for giving positive Prausnitz-Küstner reactions was estimated. Comparisons were made between the γE antibody in patients' sera and rabbit antibody specific for antigen E, with respect to the allergen-binding activity. The binding activity of γE antibody present in the minimum dose of five patients' sera required for giving positive reactions was comparable to that of 2 × 10-6 µgN of the rabbit antibody.
Mimicry diversification in Papilio dardanus via a genomic inversion in the regulatory region of engrailed–invected

Polymorphic Batesian mimics exhibit multiple protective morphs that each mimic a different noxious model. Here, we study the genomic transitions leading to the evolution of different mimetic wing patterns in the polymorphic Mocker Swallowtail Papilio dardanus. We generated a draft genome (231 Mb over 30 chromosomes) and re-sequenced individuals of three morphs. Genome-wide single nucleotide polymorphism (SNP) analysis revealed elevated linkage disequilibrium and divergence between morphs in the regulatory region of engrailed, a developmental gene previously implicated in the mimicry switch. The diverged region exhibits a discrete chromosomal inversion (of 40 kb) relative to the ancestral orientation that is associated with the cenea morph, but not with the bottom-recessive hippocoonides morph or with non-mimetic allopatric populations. The functional role of this inversion in the expression of the novel phenotype is currently unknown, but by preventing recombination, it allows the stable inheritance of divergent alleles enabling geographic spread and local coexistence of multiple adaptive morphs.
Change in geomagnetic field intensity alters migration-associated traits in a migratory insect

Geomagnetic field (GMF) intensity can be used by some animals to determine their position during migration. However, its role, if any, in mediating other migration-related phenotypes remains largely unknown. Here, we simulated variation in GMF intensity between two locations along the migration route of a nocturnal insect migrant, the brown planthopper Nilaparvata lugens, that varied by approximately 5 µT in field intensity. After one generation of exposure, we tested for changes in key morphological, behavioural and physiological traits related to migratory performance, including wing dimorphism, flight capacity and positive phototaxis. Our results showed that all three morphological and behavioural phenotypes responded to a small difference in magnetic field intensity. Consistent magnetic responses in the expression of the phototaxis-related Drosophila-like cryptochrome 1 (Cry1) gene and levels of two primary energy substrates used during flight, triglyceride and trehalose, were also found. Our findings indicate changes in GMF intensity can alter the expression of phenotypes critical for insect migration and highlight the unique role of magnetoreception as a trait that may help migratory insects express potentially beneficial phenotypes in geographically variable environments.