Miracle-dz/UniFAR-FTUs huggingface dataset:
Prospects of fish supply-demand and its implications for food and nutrition security in Egypt

Aquaculture plays an increasingly important role in meeting the rising global demand for fish fuelled by economic and demographic growth. However, in many middle income countries, the growth of aquaculture is constrained by rising labor costs, limited input supply, environmental concerns, and infectious diseases. In this paper, we developed a multi species, multi sector equilibrium model and applied it to the fishery sector of Egypt, a leading aquaculture producer in Africa, to examine these barriers. Projection results show that rising wage rates would slow down the growth of labour-intensive aquaculture compared to those that use relatively less labour. The demand for feed, seed inputs and water use for aquaculture would substantially increase. The results also show that disease outbreaks would possibly affect production sectors via output reduction and also consumers via increases in fish price. Our findings suggest that stabilising the prices of feed and seed, investments in disease control and input use efficiency improvement technologies, including water use, are important while the overall effectiveness of tax instruments is modest. Though calibrated to Egypt, our approach can be applied to other middle size national aquaculture industries.
Scientometric engineering: Exploring citation dynamics via arXiv eprints

Abstract Scholarly communications have been rapidly integrated into digitized and networked open ecosystems, where preprint servers have played a pivotal role in accelerating the knowledge transfer processes. However, quantitative evidence is scarce regarding how this paradigm shift beyond the traditional journal publication system has affected the dynamics of collective attention on science. To address this issue, we investigate the citation data of more than 1.5 million eprints on arXiv (https://arxiv.org) and analyze the long-term citation trend for each discipline involved. We find that the typical growth and obsolescence patterns vary across disciplines, reflecting different publication and communication practices. The results provide unique evidence of the attention dynamics shaped by the research community today, including the dramatic growth and fast obsolescence of Computer Science eprints, which has not been captured in previous studies relying on the citation data of journal papers. Subsequently, we develop a quantitatively and temporally normalized citation index with an approximately normal distribution, which is useful for comparing citational attention across disciplines and time periods. Further, we derive a stochastic model consistent with the observed quantitative and temporal characteristics of citation growth and obsolescence. The findings and the developed framework open a new avenue for understanding the nature of citation dynamics.
Large crop production losses induced by global ozone stress based on interval evaluation

Global crop yield loss due to ground-level ozone (O3) concentrations is a major challenge to food security, but a dose-response association is not easy to quantify. Here, we propose using a new metric, O3 sensitivity of crop yield (Yo), to estimate yield loss under different O3 time intervals using four observational databases. The Yo metric shows a non-linear parabola with elevated atmospheric O3 for wheat, maize, rice, soybean, and assorted vegetables. Spatial heterogeneity of yield loss varies as a function of crop type and O3 intervals. Estimates of yield loss from ozone suggest recent losses (2017-2019) may reach as high as 537 million tonnes, with a significant proportion coming with lower (30-40 ppb) exposure (325 million tonnes). Our results suggest that previous research, which only included higher (>40 ppb ozone), may have had grossly underestimated the negative effect of atmospheric O3 on crop production. Suppose these results are endemic to global crop production. In that case, additional research will be necessary to reassess ozone sensitivity and dose-responses, both spatially and temporally, to determine future air pollution impacts.
Localization in a HRTF-based Minimum Audible Angle Listening Test on a 2D Sound Screen for GUIB Applications

Listening tests were carried out for investigating the localization judgments of 40 untrained subjects through equalized headphones and with HRTF synthesis. The investigation was made on the basis of the former GUIB (Graphical User Interface for Blind Persons) project in order to determine the possibilities of a 2D virtual sound screen and headphone playback. Results will be presented about the capabilities and values of typical headphone playback errors as well as minimum, maximum and average values of discrimination skills. Special localization events like left-right and up-down symmetries, missing locations in vertical localization are also discussed. The measurement method includes a special 3-categorie-forced-choice MAA report on a screen-like virtual auditory surface in front of the listeners. Test signals were presented with different spectra and movement. Conclusions are drawn both for a GUIB application as well as for the binaural synthesis about the role of the fine structure of applied HRTFs.
Phytochemical compositions and antimicrobial activity of leaf extracts of Calotropis procera against food spoilage microorganisms

Background: The purpose of this study was to determine the phytochemical composition and antimicrobial potential of crude n-hexane, ethyl-acetate, methanol and aqueous extracts of Calotropis procera leaves against food spoilage microorganisms. Methods: Standard protocols were employed for the analysis of qualitative phytochemical compositions of the extracts, and antimicrobial activities against Staphylococcus aureus, Bacillus cereus, Pseudomonas aerugenosa and Aspergillus niger. Results: Phytochemical analysis revealed the presence of tannin, saponin, alkaloids, flavonoids, reducing sugar and phenolics. Terpenoids were absent in ethyl acetate and n-hexane extracts while cardiac glycoside was absent in all extracts. All extracts produced antimicrobial activity at a varying zone of inhibition. The widest inhibition zone was produced by methanol extract (21.35±0.43 mm) on staphylococcus aureus while the lowest inhibition zone (12.05±0.45 mm) was observed in the n-hexane fraction. Similarly, the widest inhibition zone (17.24±0.95 mm) was produced by methanol on A. niger while the lowest inhibition zone (5.45±0.42 mm) was produced on n-hexane on A. niger. However, the ethyl acetate extract showed no visible inhibitory zone on all the tested microorganisms. The minimum inhibitory concentration ranged from 32 mg/ml (S. aureus and B. cereus) for ethanol extracts to 128 mg/ml (B. cereus, P. aerugenosa and A. niger) for n-hexane extract. Conclusion: The result shows that the plant is a good source of bioactive compounds that can be used as a natural alternative to a chemical agent in preserving and controlling food poisoning organisms.
Human Fall Detection Using Passive Infrared Sensors with Low Resolution: A Systematic Review

Abstract Systems using passive infrared sensors with a low resolution were recently proposed to answer the dilemma effectiveness–ethical considerations for human fall detection by Information and Communication Technologies (ICTs) in older adults. How effective is this type of system? We performed a systematic review to identify studies that investigated the metrological qualities of passive infrared sensors with a maximum resolution of 16×16 pixels to identify falls. The search was conducted on PubMed, ScienceDirect, SpringerLink, IEEE Xplore Digital Library, and MDPI until November 26–28, 2020. We focused on studies testing only these types of sensor. Thirteen articles were “conference papers”, five were “original articles” and one was a found in arXiv.org (an open access repository of scientific research). Since four authors “duplicated” their study in two different journals, our review finally analyzed 15 studies. The studies were very heterogeneous with regard to experimental procedures and detection methods, which made it difficult to draw formal conclusions. All studies tested their systems in controlled conditions, mostly in empty rooms. Except for two studies, the overall performance reported for the detection of falls exceeded 85–90% of accuracy, precision, sensitivity or specificity. Systems using two or more sensors and particular detection methods (eg, 3D CNN, CNN with 10-fold cross-validation, LSTM with CNN, LSTM and Voting algorithms) seemed to give the highest levels of performance (> 90%). Future studies should test more this type of system in real-life conditions.
Evaluation of Community Pharmacists Knowledge, Attitude and Practice towards Modified Release Dosage Forms

Purpose:To evaluate knowledge, practice and attitude of community pharmacists in Basra regarding modified release dosage forms which are widely used for many therapeutic purposes in pharmacy practice. Methods:The current study was conducted among certified pharmacists in Basra governorate- south of Iraq. Data collection was carried out by a questionnaire. Results:A total number of 175 community pharmacists responded to the questionnaire. The majority worked in OTC based dispensing pharmacies located in the center of the city. Most respondents missed K1 and were unable to state the difference between different types of modified products. There was a major positive agreement towards medical representatives' rule in promoting the prescribing of modified release products by physicians. Avoiding crushing and breaking of solid oral modified release drugs were identified by the majority of participants. Correlation analysis showed a 22.8 correlation coefficient between knowledge and attitude which was statistically significant. Males showed statistically significant higher knowledge and practice scores than females. Conclusions:The conduction of a brief educational program would be very beneficial in bringing basic theoretical knowledge with practicing points of interest and promote a more positive attitude toward this unique class of novel drug delivery system.
Low-power, gigahertz clock generation and distribution using injection-locked oscillators

The generation and distribution of high speed and high quality clock signals have become increasingly important in high performance microprocessors, wireline communications and wireless communications. In multi-gigahertz frequency range, conventional clocking techniques have encountered several design challenges in terms of power consumption, skew and jitter. Injection-locking is a promising technique to address these design challenges for gigahertz clocking. This dissertation presents our studies of gigahertz, high performance, low power clock generation and distribution using injection-locked frequency dividers (ILFDs), injection-locked frequency multipliers (ILFMs) and injection-locked clock distribution networks (ILCs). Chip prototypes in 0. 18μm standard digital CMOS technologies are demonstrated for the following gigahertz clocking circuits. For gigahertz clock generation, we introduced a phase tuning scheme for an ILFDbased dual-phase signal generator. The phase tuning capability in this scheme comes from the tunable phase transfer characteristics of injection-locked frequency dividers. Implemented with a frequency-tunable double-balanced divide-by-two injection-locked frequency divider, the dual-phase signal generator prototype achieves 100 differential phase tuning range around quadrature with generated signal frequency of 5 GHz. For gigahertz frequency division, we introduced a divide-by-odd-number injectionlocked frequency divider to address the division ratio limitation of conventional injectionlocked frequency dividers. With differential injection and harmonic filtering, this new
Chemical composition and antimicrobial activity of essential oils extracted from Amomum muricarpum Elmer from North Vietnam

Abstract. Recent years have seen the development of bacterial resistance to currently available antibiotics, which necessitates a search for new antimicrobial agents. Amomum muricarpum Elmer is a widely used medicinal plant species in the genus Amomum (family Zingiberaceae) that is commonly found in Laos, the Philippines, China, and Vietnam. The present article describes the chemical composition and antimicrobial activity of essential oils extracted from the leaves and rhizomes of A. muricarpum from North Vietnam. The hydrodistilled essential oil was analyzed using gas chromatography and gas chromatography-mass spectrometry, with the broth microdilution method designed to evaluate its antimicrobial efficacy. The absolute yield of essential oils amounted to 0.11% and 0.13% (v/w) for leaves and rhizomes, respectively, on a dry weight basis. It was found that the leaves and rhizomes of A. muricarpum produce oils abounding in monoterpenes. Of the total identified volatile components in the leaf oil (97.18%), three main constituents include α-pinene (40.45%), linalool (12.34%), and β-pinene (10.31%). In the rhizome oil, the main constituents include α-pinene (48.10%), β-pinene (20.32%), and linalool (7.56%) of the total identified volatile components (98.08%). An antimicrobial activity test indicates that essential oils from the leaves and rhizome of A. muricarpum inhibit the growth of Staphylococcus aureus ATCC 25923, with a minimum inhibitory concentration (MIC) of 200 µg/ml. In addition, the rhizome essential oil also exhibits antimicrobial activity against Bacillus cereus ATCC 14579, with a MIC value of 200 µg/ml. The results indicate the potential of essential oils extracted from A. muricarpum as a source of antimicrobial agents.
Analysing Intelligence, Surveillance and Reconnaissance

We investigate our novel and new technique for analysing Intelligence, Surveillance and Reconnaissance (ISR) in military engagements. This is a small part of the work that has been carried out at the Defence Science and Technology Organisation (DSTO) and the Western Australian Centre of Excellence in Industrial Optimisation (WACEIO) to assess the value of ISR systems when the friendly operational commander is conducting Manoeuvre Warfare, which requires the friendly force that is relatively small and mobile be advantageously positioned in space and time to disrupt the strength and will to fight of the enemy force [2, 3]. Mathematical models of the ISR operations are developed for a generic engagement between the friendly and enemy forces, and then demonstrated using a maritime battle that necessitates the collection of information on the dispositions of the enemy scouts and their threats by a satellite (Option 1), an Unmanned Aerial Vehicle (UAV) (Option 2) or both of these ISR systems (Option 3) prior to commencing hostilities. For the parametric choices that define these options, the results show that Option 3 is the best, Option 1 is the second best and Option 2 is the third best. Furthermore, the results show that our technique will assist with gaining a deeper understanding of how the ISR operations impact on the operational commander's objective.
A Deep Learning Framework for Segmenting Brain Tumors Using MRI and Synthetically Generated CT Images

Multi-modal three-dimensional (3-D) image segmentation is used in many medical applications, such as disease diagnosis, treatment planning, and image-guided surgery. Although multi-modal images provide information that no single image modality alone can provide, integrating such information to be used in segmentation is a challenging task. Numerous methods have been introduced to solve the problem of multi-modal medical image segmentation in recent years. In this paper, we propose a solution for the task of brain tumor segmentation. To this end, we first introduce a method of enhancing an existing magnetic resonance imaging (MRI) dataset by generating synthetic computed tomography (CT) images. Then, we discuss a process of systematic optimization of a convolutional neural network (CNN) architecture that uses this enhanced dataset, in order to customize it for our task. Using publicly available datasets, we show that the proposed method outperforms similar existing methods.
The Role of OXT, OXTR, AVP, and AVPR1a Gene Expression in the Course of Schizophrenia

Schizophrenia is a serious and chronic mental illness, the symptoms of which usually appear for the first time in late adolescence or early adulthood. To date, much research has been conducted on the etiology of schizophrenia; however, it is still not fully understood. Oxytocin and vasopressin as neuromodulators that regulate social and emotional behavior are promising candidates for determining the vulnerability to schizophrenia. The aim of this study was to evaluate the expression of OXT, OXTR, AVP, and AVPR1a genes at the mRNA and protein levels in patients with schizophrenia. Due to the neurodegenerative nature of schizophrenia, the study group was divided into two subgroups, namely, G1 with a diagnosis that was made between 10 and 15 years after the onset of the illness, and G2 with a diagnosis made up to two years after the onset of the illness. Moreover, the relationship between the examined genes and the severity of schizophrenia symptoms, assessed using PANSS (Positive and Negative Syndrome Scale) and CDSS scales (Clinical Depression Scale for Schizophrenia) was evaluated. The analysis of the expression of the studied genes at the mRNA and protein levels showed statistically significant differences in the expression of all the investigated genes. OXT and AVPR1a gene expression at both the mRNA and protein levels were significantly lower in the schizophrenia group, and OXTR and AVP gene expression at both the mRNA and protein levels was higher in the schizophrenia subjects than in the controls. Furthermore, a significant correlation of OXT gene expression at the mRNA and protein levels with the severity of depressive symptoms in schizophrenia as assessed by CDSS was found.
A Methodological Approach on Linked Open Data Production: The Publicspending.Gr Project

Web technologies have evolved to effectively support the creation and existence of Linked Open Data (LOD) within the web. However, the production and mass consumption of LOD have been a matter of debate over methodologies, best practices, and technologies that should be employed. Particularly in the case of government LOD, the production and publication lifecycle needs to follow a methodological approach. The paper presents publicspending.gr, a 5-star LOD project focusing on Greek Public spending as a case of LD application that is developed according to a methodological approach, following a specific Linked Data Production Life Cycle.
Impact of antenna array geometry on the capacity of mimo communication system

More services and higher data rates are the demands of future wireless communication system end users. In order to accommodate these expectations while maintaining robustness against wireless impairments, contemporary technologies have to be developed. Multiple-input multiple-output (MIMO) techniques stand as a strong candidate to allow robustness against channel fading and interference as well as to enable high data rates. This dissertation investigates the impact of different array geometries on the capacity of MIMO communication systems. Five different array configurations, Uniform Linear Array, Non-Uniform Linear Array, Uniform Circular Array, Hexagonal Array and Star Array, are being used to compare their performance from capacity point of view. The expression of the capacity of a MIMO communication system is derived from an information-theoretic approach and is altered to introduce the impact of array geometry on the system capacity. Using this expression the capacities of MIMO systems with different array geometries are compared. Also the impact of increasing the number of element of the array and changing the inter-element spacing of the array elements are examined. The significant increase in achievable capacity using array of antennas at both end of the transmission link is observed to justify the ascendancy of MIMO system.
Optimal experimental designs for estimating genetic and non-genetic effects underlying infectious disease transmission

Background The spread of infectious diseases in populations is controlled by the susceptibility (propensity to acquire infection), infectivity (propensity to transmit infection), and recoverability (propensity to recover/die) of individuals. Estimating genetic risk factors for these three underlying host epidemiological traits can help reduce disease spread through genetic control strategies. Previous studies have identified important ‘disease resistance single nucleotide polymorphisms (SNPs)’, but how these affect the underlying traits is an unresolved question. Recent advances in computational statistics make it now possible to estimate the effects of SNPs on host traits from epidemic data (e.g. infection and/or recovery times of individuals or diagnostic test results). However, little is known about how to effectively design disease transmission experiments or field studies to maximise the precision with which these effects can be estimated. Results In this paper, we develop and validate analytical expressions for the precision of the estimates of SNP effects on the three above host traits for a disease transmission experiment with one or more non-interacting contact groups. Maximising these expressions leads to three distinct ‘experimental’ designs, each specifying a different set of ideal SNP genotype compositions across groups: (a) appropriate for a single contact-group, (b) a multi-group design termed “pure”, and (c) a multi-group design termed “mixed”, where ‘pure’ and ‘mixed’ refer to groupings that consist of individuals with uniformly the same or different SNP genotypes, respectively. Precision estimates for susceptibility and recoverability were found to be less sensitive to the experimental design than estimates for infectivity. Whereas the analytical expressions suggest that the multi-group pure and mixed designs estimate SNP effects with similar precision, the mixed design is preferred because it uses information from naturally-occurring rather than artificial infections. The same design principles apply to estimates of the epidemiological impact of other categorical fixed effects, such as breed, line, family, sex, or vaccination status. Estimation of SNP effect precisions from a given experimental setup is implemented in an online software tool SIRE-PC . Conclusions Methodology was developed to aid the design of disease transmission experiments for estimating the effect of individual SNPs and other categorical variables that underlie host susceptibility, infectivity and recoverability. Designs that maximize the precision of estimates were derived.