Search results for: animal artificial insemination

Authors: Karen L. Middlemiss, Denham G. Cook, Peter Jaksons, Alistair Jerrett, William Davison

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Lateralisation of cognitive function is a common phenomenon found throughout the animal kingdom. Strong biases in functional behaviours have evolved from asymmetrical brain hemispheres which differ in structure and/or cognitive function. In fish, lateralisation is involved in visually mediated behaviours such as schooling, predator avoidance, and foraging, and is considered to have a direct impact on species fitness. Currently, there is very little literature on the role of lateralisation in fish schools. The yellow-eyed mullet (Aldrichetta forsteri), is an estuarine and coastal species found commonly throughout temperate regions of Australia and New Zealand. This study sought to quantify visually mediated behaviours in yellow-eyed mullet to identify the significance of lateralisation, and the factors which influence functional behaviours in schooling fish. Our approach to study design was to conduct a series of tank based experiments investigating; a) individual and population level lateralisation, b) schooling behaviour, and d) optic lobe anatomy. Yellow-eyed mullet showed individual variation in direction and strength of lateralisation in juveniles, and trait specific spatial positioning within the school was evidenced in strongly lateralised fish. In combination with observed differences in schooling behaviour, the possibility of ontogenetic plasticity in both behavioural lateralisation and optic lobe morphology in adults is suggested. These findings highlight the need for research into the genetic and environmental factors (epigenetics) which drive functional behaviours such as schooling, feeding and aggression. Improved knowledge on collective behaviour could have significant benefits to captive rearing programmes through improved culture techniques and will add to the limited body of knowledge on the complex ecophysiological interactions present in our inshore fisheries.

Keywords: cerebral asymmetry, fisheries, schooling, visual bias

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Authors: Sheng Yu Chen, Shi-Heng Wang

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Aim: Based on human, animal experiments, and genetic studies, cysteinyl leukotrienes, LTC4, LTD4, and LTE4, are inflammatory substances that are metabolized by 5-lipooxygenase from arachidonic acid, and these substances trigger asthma. In addition, the synthetic pathway of cysteinyl leukotriene is relevant to the increase in cardiovascular diseases such as myocardial ischemia and stroke. Given the situation, we aim to investigate whether cysteinyl leukotrienes receptor antagonist (LTRA), montelukast which cures those who have asthma has potential protective effects on cardiovascular diseases. Method: We conducted a cohort study, and enrolled participants which are newly diagnosed with asthma (ICD-9 CM code 493. X) between 2002 to 2011. The data source is from Taiwan National Health Insurance Research Database Patients with a previous history of myocardial infarction or ischemic stroke were excluded. Among the remaining participants, every montelukast user was matched with two randomly non-users by sex, and age. The incident cardiovascular diseases, including myocardial infarction and ischemic stroke, were regarded as outcomes. We followed the participants until outcomes come first or the end of the following period. To explore the protective effect of montelukast on the risk of cardiovascular disease, we use multivariable Cox regression to estimate the hazard ratio with adjustment for potential confounding factors. Result: There are 55876 newly diagnosed asthma patients who had at least one claim of inpatient admission or at least three claims of outpatient records. We enrolled 5350 montelukast users and 10700 non-users in this cohort study. The following mean (±SD) time of the Montelukast group is 5 (±2.19 )years, and the non-users group is 6.2 5.47 (± 2.641) years. By using multivariable Cox regression, our analysis indicated that the risk of incident cardiovascular diseases between montelukast users (n=43, 0.8%) and non-users (n=111, 1.04%) is approximately equal. [adjusted hazard ratio 0.992; P-value:0.9643] Conclusion: In this population-based study, we found that the use of montelukast is not associated with a decrease in incident MI or IS.

Keywords: asthma, inflammation, montelukast, insurance research database, cardiovascular diseases

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Authors: Sakeh N. Mohd, Bahari M. N. Abdul, Abdullah S. N. Akmar

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Oil palm production generates high export earnings to many countries especially in Southeast Asian region. Infection by necrotrophic fungus, Ganoderma boninense on oil palm results in basal stem rot which compromises oil palm production leading to significant economic loss. There are no reliable disease treatments nor promising resistant oil palm variety has been cultivated to eradicate the disease up to date. Thus, understanding molecular mechanisms underlying early interactions of oil palm with Ganoderma boninense may be vital to promote preventive or control measure of the disease. In the present study, four months old oil palm seedlings were infected via artificial inoculation of Ganoderma boninense on rubber wood blocks. Roots of six biological replicates of treated and untreated oil palm seedlings were harvested at 0, 3, 7 and 11 days post inoculation. Next-generation sequencing was performed to generate high-throughput RNA-Seq data and identify differentially expressed genes (DEGs) during early oil palm-Ganoderma boninense interaction. Based on de novo transcriptome assembly, a total of 427,122,605 paired-end clean reads were assembled into 30,654 unigenes. DEGs analysis revealed upregulation of 173 transcription factors on Ganoderma boninense-treated oil palm seedlings. Sixty-one transcription factors were categorized as DEGs according to stringent cut-off values of genes with log2 ratio [Number of treated oil palm seedlings/ Number of untreated oil palm seedlings] ≥ |1.0| (corresponding to 2-fold or more upregulation) and P-value ≤ 0.01. Transcription factors in response to biotic stress will be screened out from abiotic stress using reverse transcriptase polymerase chain reaction. Transcription factors unique to biotic stress will be verified using real-time polymerase chain reaction. The findings will help researchers to pinpoint defense response mechanism specific against Ganoderma boninense.

Keywords: Ganoderma boninense, necrotrophic, next-generation sequencing, transcription factors

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Authors: Badrane Nohayla, Bamousse Zineb

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Financial crises, exchange rate volatility, fluctuations in commodity prices, increased competitive pressures, and environmental issues are all threats that businesses face. In light of these diverse challenges, proactive, agile, and innovative cash management becomes an indispensable financial shield, allowing companies to thrive despite the adverse conditions of the global environment. In the same spirit, uncertainty, turbulence, volatility, and competitiveness continue to disrupt economic environments, compelling companies to swiftly master innovative breakthroughs that provide added value. In such a context, innovation emerges as a catalytic vector for performance, aiming to reduce costs, strengthen growth, and ultimately ensure the sustainability of Moroccan companies in the national arena. Moreover, innovation in treasury management promises to be one of the key pillars of financial stability, enabling companies to navigate the tumultuous waters of a globalized environment. Therefore, the objective of this study is to better understand the impact of innovative treasury management on cost optimization and, by extension, performance improvement. To elucidate this relationship, we conducted an exploratory qualitative study with 20 large Moroccan companies operating in the Casablanca-Settat region. The results highlight that innovation at the heart of treasury management is a guarantee of sustainability against the risks of failure and stands as a true pivot of the performance of Moroccan companies, an important parameter of their financial balance and a catalytic vector of their growth in the national economic landscape. In this regard, this study aims to provide answers to the following question: To what extent does innovation at the core of the treasury function prove to be the indispensable shield to boost performance while optimizing costs for large Moroccan companies?

Keywords: innovative cash management, artificial intelligence (ai), financial performance, risk management, cost savings

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Authors: Syed Dawood Md. Taimur, Md. Hasanur Rahman, Syeda Fahmida Afrin, Farzana Islam

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The concept of myocardial injury, although first recognized from animal studies, is now recognized as a clinical phenomenon that may result in microvascular damage, no-reflow phenomenon, myocardial stunning, myocardial hibernation and ischemic preconditioning. The final consequence of this event is left ventricular (LV) systolic dysfunction leading to increased morbidity and mortality. The typical clinical case of reperfusion injury occurs in acute myocardial infarction (MI) with ST segment elevation in which an occlusion of a major epicardial coronary artery is followed by recanalization of the artery. This may occur either spontaneously or by means of thrombolysis and/or by primary percutaneous coronary intervention (PCI) with efficient platelet inhibition by aspirin (acetylsalicylic acid), clopidogrel and glycoprotein IIb/IIIa inhibitors. In recent years, percutaneous coronary intervention (PCI) has become a well-established technique for the treatment of coronary artery disease. PCI improves symptoms in patients with coronary artery disease and it has been increasing the safety of procedures. However, peri- and post-procedural myocardial injury, including angiographical slow coronary flow, microvascular embolization, and elevated levels of cardiac enzyme, such as creatine kinase and troponin-T and -I, has also been reported even in elective cases. Furthermore, myocardial reperfusion injury at the beginning of myocardial reperfusion, which causes tissue damage and cardiac dysfunction, may occur in cases of the acute coronary syndrome. Because patients with myocardial injury is related to larger myocardial infarction and have a worse long-term prognosis than those without myocardial injury, it is important to prevent myocardial injury during and/or after PCI in patients with coronary artery disease. To date, many studies have demonstrated that adjunctive pharmacological treatment suppresses myocardial injury and increases coronary blood flow during PCI procedures. In this review, we highlight the usefulness of pharmacological treatment in combination with PCI in attenuating myocardial injury in patients with coronary artery disease.

Keywords: coronary artery disease, percutaneous coronary intervention, myocardial injury, pharmacology

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Authors: Sezer Kefeli, Sertaç Arslan

Abstract:

In this paper, supercavitationphenomena, and parameters are explained, and hydrodynamic design approaches are investigated for supercavitating torpedoes. In addition, drag force calculation methods ofsupercavitatingvehicles are obtained. Basically, conventional heavyweight torpedoes reach up to ~50 knots by classic hydrodynamic techniques, on the other hand super cavitating torpedoes may reach up to ~200 knots, theoretically. However, in order to reachhigh speeds, hydrodynamic viscous forces have to be reduced or eliminated completely. This necessity is revived the supercavitation phenomena that is implemented to conventional torpedoes. Supercavitation is a type of cavitation, after all, it is more stable and continuous than other cavitation types. The general principle of supercavitation is to separate the underwater vehicle from water phase by surrounding the vehicle with cavitation bubbles. This situation allows the torpedo to operate at high speeds through the water being fully developed cavitation. Conventional torpedoes are entitled as supercavitating torpedoes when the torpedo moves in a cavity envelope due to cavitator in the nose section and solid fuel rocket engine in the rear section. There are two types of supercavitation phase, these are natural and artificial cavitation phases. In this study, natural cavitation is investigated on the disk cavitators based on numerical methods. Once the supercavitation characteristics and drag reduction of natural cavitationare studied on CFD platform, results are verified with the empirical equations. As supercavitation parameters cavitation number (), pressure distribution along axial axes, drag coefficient (C_?) and drag force (D), cavity wall velocity (U_?) and dimensionless cavity shape parameters, which are cavity length (L_?/d_?), cavity diameter(d_ₘ/d_?) and cavity fineness ratio (〖L_?/d〗_ₘ) are investigated and compared with empirical results. This paper has the characteristics of feasibility study to carry out numerical solutions of the supercavitation phenomena comparing with empirical equations.

Keywords: CFD, cavity envelope, high speed underwater vehicles, supercavitating flows, supercavitation, drag reduction, supercavitation parameters

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Authors: Nathaniel Deboever, Malcolm Breeze, Adrian Sheen

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Basic surgical and suturing techniques are a fundamental requirement for all doctors. In order to gain confidence and competence, doctors in training need to obtain sufficient teaching and just as importantly: practice. Young doctors with an apt level of expertise on these simple surgical skills, which are often used in the Emergency Department, can help alleviate some pressure during a busy evening. Unfortunately, learning these skills can be quite difficult during medical school or even during junior doctor years. The aim of this project was to adequately train medical students attending University of Sydney’s Nepean Clinical School through a series of workshops highlighting practical skills, with hopes to further extend this program to junior doctors in the hospital. The sessions instructed basic skills via tutorials, demonstrations, and lastly, the sessions cemented these proficiencies with practical sessions. During such an endeavor, it is fundamental to employ models that appropriately resemble what students will encounter in the clinical setting. The sustainability of workshops is similarly important to the continuity of such a program. To address both these challenges, the authors have developed models including suturing platforms, knot tying, and vessel ligation stations, as well as a shave and punch biopsy models and ophthalmologic foreign body device. The unique aspect of this work is that we utilized hands-on teaching sessions, to address a gap in doctors-in-training and junior doctor curriculum. Presented to you through this poster are our approaches to creating models that do not employ animal products and therefore do not necessitate particular facilities or discarding requirements. Covering numerous skills that would be beneficial to all young doctors, these models are easily replicable and affordable. This exciting work allows for countless sessions at low cost, providing enough practice for students to perform these skills confidently as it has been shown through attendee questionnaires.

Keywords: medical education, surgical models, surgical simulation, surgical skills education

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Authors: Marah Joy A. Nanglegan

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A survey was conducted to describe knowledge, attitude, practices, information needs, and information seeking behavior of small-scale farmers on Organic Agriculture Production (OAP) in a rural community in Ifugao, Philippines. Respondents’ age ranged from 23-67 years old. Most of them are male, married, and have reached high school level. The major source of income is farming with an average monthly income of less than Php 5,000 for a household size of seven. More than fifty percent of the respondents are members of a farmer’s organization. Farm size is less than one hectare. Majority of them own their farms and have been farming for more than twenty years. Very few attended training on Organic Agriculture Production (OAP). Most of them are not aware of any OAP program in their community. Hence, their farming practices are mostly conventional. The overall level of knowledge on OAP among all respondents was below the average. On attitude, most of the respondents agreed that organic farming would decrease production costs by reducing input purchases. They believe it benefits both the consumer and the producer. In fact, they are aware of the many benefits of organic farming, especially on health. Likewise, many of them agreed on the benefits of organic farming to soil fertility, to the environment, and to increase the income of farmers. Many of them, however, see organic farming as troublesome and difficult in terms of time and effort, obtaining organic inputs, limited production, and marketing aspects. They also have heavy reliance on pesticides and herbicides to control pests and diseases. On practices, majority of the respondents stated that they practiced crop rotation, manual weeding, and the use of animal manure. Most of them desired to do organic farming but needed information such as production techniques, costs, and marketing opportunities. Their most preferred communication channel is through extension agents and contact farmers. Their most preferred communication method is through trainings and seminars as well as through farm demonstrations. Results of this study will serve as a basis for developing appropriate communication strategies to improve knowledge, attitude, and practices of respondents on organic agriculture as well as enhance the promotion of organic agriculture production in the community.

Keywords: Ifugao, knowledge attitude practices, organic agriculture, Philippines

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Authors: Loubna Khalile, Hicham Lahlaoi, Hassan Rhinane, A. Kaoukaya, S. Fal

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Green spaces is an essential element, they contribute to improving the quality of lives of the towns around them. They are a place of relaxation, walk and rest a playground for sport and youths. According to United Nations Organization Forests cover 31% of the land. In Morocco in 2013 that cover 12.65 % of the total land area, still, a small proportion compared to the natural needs of forests as a green lung of our planet. The Benslimane Forest is a large green area It belongs to Chaouia-Ouardigha Region and Greater Casablanca Region, it is located geographically between Casablanca is considered the economic and business Capital of Morocco and Rabat the national political capital, with an area of 12261.80 Hectares. The essential problem usually encountered in suburban forests, is visitation and tourism pressure it is anthropogenic actions, as well as other ecological and environmental factors. In recent decades, Morocco has experienced a drought year that has influenced the forest with increasing human pressure and every day it suffers heavy losses, as well as over-exploitation. The Moroccan forest ecosystems are weak with intense ecological variation, domanial and imposed usage rights granted to the population; forests are experiencing a significant deterioration due to forgetfulness and immoderate use of forest resources which can influence the destruction of animal habitats, vegetation, water cycle and climate. The purpose of this study is to make a model of the degree of degradation of the forest and know the causes for prevention by using remote sensing and geographic information systems by introducing climate and ancillary data. Analytic hierarchy process was used to find out the degree of influence and the weight of each parameter, in this case, it is found that anthropogenic activities have a fairly significant impact has thus influenced the climate.

Keywords: analytic hierarchy process, degradation, forest, geographic information system

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Authors: Soledad Carinelli, Iñigo Fernández, José Luis González-Mora, Pedro A. Salazar-Carballo

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Mastitis is the most relevant inflammatory disease in cattle, affecting the animal health and causing important economic losses on dairy farms. This disease takes place in the mammary gland or udder when some opportunistic microorganisms, such as Staphylococcus aureus, Streptococcus agalactiae, Corynebacterium bovis, etc., invade the teat canal. According to the severity of the inflammation, mastitis can be classified as sub-clinical, clinical and chronic. Standard methods for mastitis detection include counts of somatic cells, cell culture, electrical conductivity of the milk, and California test (evaluation of “gel-like” matrix consistency after cell lysed with detergents). However, these assays present some limitations for accurate detection of subclinical mastitis. Currently, haptoglobin, an acute phase protein, has been proposed as novel and effective biomarker for mastitis detection. In this work, an electrochemical biosensor based on polydopamine-modified magnetic nanoparticles (MNPs@pDA) for haptoglobin detection is reported. Thus, MNPs@pDA has been synthesized by our group and functionalized with hemoglobin due to its high affinity to haptoglobin protein. The protein was labeled with specific antibodies modified with alkaline phosphatase enzyme for its electrochemical detection using an electroactive substrate (1-naphthyl phosphate) by differential pulse voltammetry. After the optimization of assay parameters, the haptoglobin determination was evaluated in milk. The strategy presented in this work shows a wide range of detection, achieving a limit of detection of 43 ng/mL. The accuracy of the strategy was determined by recovery assays, being of 84 and 94.5% for two Hp levels around the cut off value. Milk real samples were tested and the prediction capacity of the electrochemical biosensor was compared with a Haptoglobin commercial ELISA kit. The performance of the assay has demonstrated this strategy is an excellent and real alternative as screen method for sub-clinical bovine mastitis detection.

Keywords: bovine mastitis, haptoglobin, electrochemistry, magnetic nanoparticles, polydopamine

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Authors: Lufungula Osembe

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The field of education has witnessed advances in technology and digital transformation. The methods of teaching have undergone significant changes in recent years, resulting in effects on various areas such as pedagogies, curriculum design, personalized teaching, gamification, data analytics, cloud-based learning applications, artificial intelligence tools, advanced plug-ins in LMS, and the emergence of multimedia creation and design. The field of education has not been immune to the changes brought about by digital innovation in recent years, similar to other fields such as engineering, health, science, and technology. There is a need to look at the variables/elements that digital innovation brings to education and develop a framework for higher institutions of learning to assess their readiness to create a viable environment for digital innovation to be successfully adopted. Given the potential benefits of digital innovation in education, it is essential to develop a framework that can assist academics and policymakers in higher institutions of learning to evaluate the effectiveness of adopting and adapting to the evolving landscape of digital innovation in education. The primary research question addressed in this study is to establish the preparedness of higher institutions of learning to adopt and adapt to the evolving landscape of digital innovation. This study follows a Design Science Research (DSR) paradigm to develop a framework for academics and policymakers in higher institutions of learning to evaluate the readiness of their institutions to adopt digital innovation in education. The Design Science Research paradigm is proposed to aid in developing a readiness framework for digital innovation in education. This study intends to follow the Design Science Research (DSR) methodology, which includes problem awareness, suggestion, development, evaluation, and conclusion. One of the major contributions of this study will be the development of the framework for digital innovation in education. Given the various opportunities offered by digital innovation in recent years, the need to create a readiness framework for digital innovation will play a crucial role in guiding academics and policymakers in their quest to align with emerging technologies facilitated by digital innovation in education.

Keywords: digital innovation, DSR, education, opportunities, research

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Authors: N. N. Mosola, S. J. Molete, L. S. Masoebe, M. Letsae

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Hand gesture recognition is a technique used to locate, detect, and recognize a hand gesture. Detection and recognition are concepts of Artificial Intelligence (AI). AI concepts are applicable in Human Computer Interaction (HCI), Expert systems (ES), etc. Hand gesture recognition can be used in sign language interpretation. Sign language is a visual communication tool. This tool is used mostly by deaf societies and those with speech disorder. Communication barriers exist when societies with speech disorder interact with others. This research aims to build a hand recognition system for Lesotho’s Sesotho and English language interpretation. The system will help to bridge the communication problems encountered by the mentioned societies. The system has various processing modules. The modules consist of a hand detection engine, image processing engine, feature extraction, and sign recognition. Detection is a process of identifying an object. The proposed system uses Canny pruning Haar and Haarcascade detection algorithms. Canny pruning implements the Canny edge detection. This is an optimal image processing algorithm. It is used to detect edges of an object. The system employs a skin detection algorithm. The skin detection performs background subtraction, computes the convex hull, and the centroid to assist in the detection process. Recognition is a process of gesture classification. Template matching classifies each hand gesture in real-time. The system was tested using various experiments. The results obtained show that time, distance, and light are factors that affect the rate of detection and ultimately recognition. Detection rate is directly proportional to the distance of the hand from the camera. Different lighting conditions were considered. The more the light intensity, the faster the detection rate. Based on the results obtained from this research, the applied methodologies are efficient and provide a plausible solution towards a light-weight, inexpensive system which can be used for sign language interpretation.

Keywords: canny pruning, hand recognition, machine learning, skin tracking

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Authors: Irsa Ejaz, Siyang He, Wei Li, Naiyue Hu, Chaochen Tang, Songbo Li, Meng Li, Boubacar Diallo, Guanghui Xie, Kang Yu

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Background: Near-infrared spectroscopy (NIR) is a non-destructive, fast, and low-cost method to measure the grain quality of different cereals. Previously reported NIR model calibrations using the whole grain spectra had moderate accuracy. Improved predictions are achievable by using the spectra of whole grains, when compared with the use of spectra collected from the flour samples. However, the feasibility for determining the critical biochemicals, related to the classifications for food, feed, and fuel products are not adequately investigated. Objectives: To evaluate the feasibility of using NIRS and the influence of four sample types (whole grains, flours, hulled grain flours, and hull-less grain flours) on the prediction of chemical components to improve the grain sorting efficiency for human food, animal feed, and biofuel. Methods: NIR was applied in this study to determine the eight biochemicals in four types of sorghum samples: hulled grain flours, hull-less grain flours, whole grains, and grain flours. A total of 20 hybrids of sorghum grains were selected from the two locations in China. Followed by NIR spectral and wet-chemically measured biochemical data, partial least squares regression (PLSR) was used to construct the prediction models. Results: The results showed that sorghum grain morphology and sample format affected the prediction of biochemicals. Using NIR data of grain flours generally improved the prediction compared with the use of NIR data of whole grains. In addition, using the spectra of whole grains enabled comparable predictions, which are recommended when a non-destructive and rapid analysis is required. Compared with the hulled grain flours, hull-less grain flours allowed for improved predictions for tannin, cellulose, and hemicellulose using NIR data. Conclusion: The established PLSR models could enable food, feed, and fuel producers to efficiently evaluate a large number of samples by predicting the required biochemical components in sorghum grains without destruction.

Keywords: FT-NIR, sorghum grains, biochemical composition, food, feed, fuel, PLSR

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Authors: Amr A. El Hanafy, Yasser M. Saad, Saleh A. Alkarim, Hussein A. Almehdar, Elrashdy M. Redwan

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Camels are substantial providers of transport, milk, sport, meat, shelter, fuel, security and capital in many countries, particularly Saudi Arabia. Identification of animal breeds has progressed rapidly during the last decade. Advanced molecular techniques are playing a significant role in breeding or strain protection laws. On the other hand, fingerprinting of some molecular markers related to some productive traits in farm animals represents most important studies to our knowledge, which aim to conserve these local genetic resources, and to the genetic improvement of such local breeds by selective programs depending on gene markers. Milk records were taken two days in each week from female camels of Majahem, Safara, Wathaha, and Hamara breeds, respectively from different private farms in northern Jeddah, Riyadh and Alwagh governorates and average weekly yields were calculated. DNA sequencing for CSN2 gene was used for evaluating the genetic variations and calculating the genetic distance values among four Saudi camel populations which are Hamra(R), Safra(Y), Wadha(W) and Majaheim(M). In addition, this marker was analyzed for reconstructing the Neighbor joining tree among evaluating camel breeds. In respect to milk yield during winter season, result indicated that average weekly milk yield of Safara camel breed (30.05 Kg/week) is significantly (p < 0.05) lower than the other 3 breeds which ranged from 39.68 for Hamara to 42.42 Kg/week for Majahem, while there are not significant differences between these three breeds. The Neighbor Joining analysis that re-constructed based on DNA variations showed that samples are clustered into two unique clades. The first clade includes Y (from Y4 to Y18) and M (from M1, to M9). On the other hand, the second cluster is including all R (from R1 to R6) and W (from W1 to W6). The genetic distance values were equal 0.0068 (between the groups M&Y and R&W) and equal 0 (within each group).

Keywords: milk yield, beta-casein precursor (CSN2), Saudi camel, molecular markers

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Authors: Cosmas Pandit Pagwiwoko, Ammar Khaled Abdelaziz Abdelsamia

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Flutter as a phenomenon of flow-induced and self-excited vibration has to be recognized considering its harmful effect on the structure especially in a stage of aircraft design. This phenomenon is also important for a wind energy harvester based on the fluttering surface due to its effective operational velocity range. This multi-physics occurrence can be presented by two governing equations in both fluid and structure simultaneously in respecting certain boundary conditions on the surface of the body. In this work, the equations are resolved separately by two distinct solvers, one-time step of each domain. The modelling and simulation of this flow-structure interaction in ANSYS show the effectiveness of this loosely coupled method in representing flutter phenomenon however the process is time-consuming for design purposes. Therefore, another technique using the same weak coupled aero-structure is proposed by using system dynamics approach. In this technique, the aerodynamic forces were calculated using singularity function for a range of frequencies and certain natural mode shapes are transformed into time domain by employing an approximation model of fraction rational function in Laplace variable. The representation of structure in a multi-degree-of-freedom coupled with a transfer function of aerodynamic forces can then be simulated in time domain on a block-diagram platform such as Simulink MATLAB. The dynamic response of flutter at certain velocity can be evaluated with another established flutter calculation in frequency domain k-method. In this method, a parameter of artificial structural damping is inserted in the equation of motion to assure the energy balance of flow and vibrating structure. The simulation in time domain is particularly interested as it enables to apply the structural non-linear factors accurately. Experimental tests on a fluttering airfoil in the wind tunnel are also conducted to validate the method.

Keywords: flutter, flow-induced vibration, flow-structure interaction, non-linear structure

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Authors: Hira Lal Gope, Hidekazu Fukai

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The aim of this study is to develop a system which can identify and sort peaberries automatically at low cost for coffee producers in developing countries. In this paper, the focus is on the classification of peaberries and normal coffee beans using image processing and machine learning techniques. The peaberry is not bad and not a normal bean. The peaberry is born in an only single seed, relatively round seed from a coffee cherry instead of the usual flat-sided pair of beans. It has another value and flavor. To make the taste of the coffee better, it is necessary to separate the peaberry and normal bean before green coffee beans roasting. Otherwise, the taste of total beans will be mixed, and it will be bad. In roaster procedure time, all the beans shape, size, and weight must be unique; otherwise, the larger bean will take more time for roasting inside. The peaberry has a different size and different shape even though they have the same weight as normal beans. The peaberry roasts slower than other normal beans. Therefore, neither technique provides a good option to select the peaberries. Defect beans, e.g., sour, broken, black, and fade bean, are easy to check and pick up manually by hand. On the other hand, the peaberry pick up is very difficult even for trained specialists because the shape and color of the peaberry are similar to normal beans. In this study, we use image processing and machine learning techniques to discriminate the normal and peaberry bean as a part of the sorting system. As the first step, we applied Deep Convolutional Neural Networks (CNN) and Support Vector Machine (SVM) as machine learning techniques to discriminate the peaberry and normal bean. As a result, better performance was obtained with CNN than with SVM for the discrimination of the peaberry. The trained artificial neural network with high performance CPU and GPU in this work will be simply installed into the inexpensive and low in calculation Raspberry Pi system. We assume that this system will be used in under developed countries. The study evaluates and compares the feasibility of the methods in terms of accuracy of classification and processing speed.

Keywords: convolutional neural networks, coffee bean, peaberry, sorting, support vector machine

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Authors: Ziaul Islam, Asad Sultan, Sarzamin Khan

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Organic acids and micro encapsulated phyto essential oils have revealed great potential as an antibiotic replacement and as an additive to work tremendously for the health maintenance of broiler chicken. To explore more about organic acids, a total of 600 day-old broiler chicks (Cobb-500) were procured from a local hatchery and distributed into 5 treatment groups having 6 replicates of 20 birds each; the duration of the biological trial was of 35 days. Group T1 served as a control group that were fed on corn soy-based diet only. T2 were fed with a diet having 6% poultry by-product meal (PBM) diet, T3, T4, and T5 were served as the same diet as T2 but supplemented with an organic acid, phyto essential oils alone, and a combination, respectively. The findings declared significant improvement (p<0.05) in body weight gain and FCR in groups T3, T4, and T5 while feed intake was not affected. European broiler performance indicators like production efficiency factor (EPEF) and broiler index (EBI) were improved significantly (p<0.05) by the treatments T3, T4, and T5 compared with T1 and T2. Carcass evaluation depicted significantly better (p<0.05) dressed and eviscerated weight along with carcass yield (T3, T4, T5). Broilers fed organic acid and phyto essential oils supplemented diet had significantly lower (p<0.05) Clostridium perfringens, Escherichia coliand Salmonella and increased Lactobacillus counts. Likewise, antibody titer against ND, IB, and IBD were also significantly (p<0.05) improved by the treatments T3, T4 and T5compared with the T1and T2. Litter moisture content was significantly (p<0.05) reduced by treatmentsT3, T4, and T5 on day 28 and 35 compared with the T1 and T2. These findings of the present study revealed that supplementation of organic acids blend and phyto-essential oils as an as an substitute to improve the performance of broilers without the use of feed antibiotics in broilers fed with 6% poultry by-product meal based diet.

Keywords: organic acid, phyto essential oils, growth performance, PBM, gut health, microbiota, immunity

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Authors: Zeina Merabi, Arij Dao

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The temporal order of information processing in the brain is an important code in many acoustic signals, including speech, music, and animal vocalizations. Despite its significance, surprisingly little is known about its underlying cellular mechanisms and network manifestations. In the songbird telencephalic nucleus HVC, a subset of neurons shows temporal combination sensitivity (TCS). These neurons show a high temporal specificity, responding differently to distinct patterns of spectral elements and their combinations. HVC neuron types include basal-ganglia-projecting HVCX, forebrain-projecting HVCRA, and interneurons (HVC¬INT), each exhibiting distinct cellular, electrophysiological and functional properties. In this work, we develop conductance-based neural network models connecting the different classes of HVC neurons via different wiring scenarios, aiming to explore possible neural mechanisms that orchestrate the combination sensitivity property exhibited by HVCX, as well as replicating in vivo firing patterns observed when TCS neurons are presented with various auditory stimuli. The ionic and synaptic currents for each class of neurons that are presented in our networks and are based on pharmacological studies, rendering our networks biologically plausible. We present for the first time several realistic scenarios in which the different types of HVC neurons can interact to produce this behavior. The different networks highlight neural mechanisms that could potentially help to explain some aspects of combination sensitivity, including 1) interplay between inhibitory interneurons’ activity and the post inhibitory firing of the HVCX neurons enabled by T-type Ca2+ and H currents, 2) temporal summation of synaptic inputs at the TCS site of opposing signals that are time-and frequency- dependent, and 3) reciprocal inhibitory and excitatory loops as a potent mechanism to encode information over many milliseconds. The result is a plausible network model characterizing auditory processing in HVC. Our next step is to test the predictions of the model.

Keywords: combination sensitivity, songbirds, neural networks, spatiotemporal integration

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Authors: Paulina Pergoł, Paulina Pergoł, Tomasz Kryczka

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Aging of societies is a phenomenon that is visible all over the world. The above has social, economic, and medical consequences. Many methods of pro-health stimulation of the elderly, improving cognitive functions and quality of life, are described in the world literature. The most frequently used method of activating the elderly is physical activity, in which, in addition to standard exercise programs, activities such as dance, tai chi, and yoga are often introduced. The introduction of physical activity may be limited due to the disability that often accompanies people aged 65+. Other activating methods mentioned in the literature are therapies with the participation of animals - animal therapy or plant therapy - hortitherapy, as well as music therapy, which is increasingly popular. All of the above-mentioned therapeutic methods require the involvement of a person who would conduct the so-called occupational therapist, which can be a financial barrier for many nursing homes. Researchers all over the world are trying to find solutions that can be applied in any care institution, even in those where financial support for running such centers is small. One of the forms of therapy that is recommended in the group of elderly people and which does not require large financial outlays is the so-called reminiscence therapy based on recalling personal experiences and experiences. Thanks to reminiscence therapy, seniors can return to happy moments in their lives. Research shows that reminiscence therapy increases self-esteem and reduces symptoms of depression. The method of activating older people with the use of correspondence can be an effective and low-cost form of therapy, as shown by the pilot study conducted in 2019 as part of the Queen Silvia Nursing Award competition, consisting in a systematic exchange of correspondence between volunteers and residents of the Nursing Home. This study was conducted with the participation of a small group of participants, therefore, in order to identify and prove the beneficial effect of this form of activation, it should be carried out on a larger group of respondents using standardized scales assessing various psychological parameters.

Keywords: nursing, elderly care, psychiatry, psychology

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Authors: Orit Wolf

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Classical music confronts a crucial challenge: updating cherished concert traditions for the digital age. This paper is a journey, and a quest to make classical concerts resonate with a new generation. It's not just about asking questions; it's about exploring the future of classical concerts and their potential to captivate and connect with today's audience in an era defined by change. The younger generation, known for their love of diversity, interactive experiences, and multi-sensory immersion, cannot be overlooked. This paper explores innovative strategies that forge deep connections with audiences whose relationship with classical music differs from the past. The urgency of this challenge drives the transformation of classical concerts. Examining classical concerts is necessary to understand how they can harmonize with contemporary sensibilities. New dimensions in audiovisual experiences that enchant the emerging generation are sought. Classical music must embrace the technological era while staying open to fusion and cross-cultural collaboration possibilities. The role of technology and Artificial Intelligence (AI) in reshaping classical concerts is under research. The fusion of classical music with digital experiences and dynamic interdisciplinary collaborations breathes new life into the concert experience. It aligns classical music with the expectations of modern audiences, making it more relevant and engaging. Exploration extends to the structure of classical concerts. Conventions are challenged, and ways to make classical concerts more accessible and captivating are sought. Inspired by innovative artistic collaborations, musical genres and styles are redefined, transforming the relationship between performers and the audience. This paper, therefore, aims to be a catalyst for dialogue and a beacon of innovation. A set of critical inquiries integral to reshaping classical concerts for the digital age is presented. As the world embraces digital transformation, classical music seeks resonance with contemporary audiences, redefining the concert experience while remaining true to its roots and embracing revolutions in the digital age.

Keywords: new concert formats, reception of classical music, interdiscplinary concerts, innovation in the new musical era, mash-up, cross culture, innovative concerts, engaging musical performances

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Authors: Abu Yousuf, Maksudur Rahman Khan, Ahasanul Karim, Amirul Islam, Minhaj Uddin Monir, Sharmin Sultana, Domenico Pirozzi

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Traditional biodiesel feedstock like edible oils or plant oils, animal fats and cooking waste oil have been replaced by microbial oil in recent research of biodiesel synthesis. The well-known community of microbial oil producers includes microalgae, oleaginous yeast and seaweeds. Conventional transesterification of microbial oil to produce biodiesel is lethargic, energy consuming, cost-ineffective and environmentally unhealthy. This process follows several steps such as microbial biomass drying, cell disruption, oil extraction, solvent recovery, oil separation and transesterification. Therefore, direct transesterification of biodiesel synthesis has been studying for last few years. It combines all the steps in a single reactor and it eliminates the steps of biomass drying, oil extraction and separation from solvent. Apparently, it seems to be cost-effective and faster process but number of difficulties need to be solved to make it large scale applicable. The main challenges are microbial cell disruption in bulk volume and make faster the esterification reaction, because water contents of the medium sluggish the reaction rate. Several methods have been proposed but none of them is up to the level to implement in large scale. It is still a great challenge to extract maximum lipid from microbial cells (yeast, fungi, algae) investing minimum energy. Electroporation technique results a significant increase in cell conductivity and permeability caused due to the application of an external electric field. Electroporation is required to alter the size and structure of the cells to increase their porosity as well as to disrupt the microbial cell walls within few seconds to leak out the intracellular lipid to the solution. Therefore, incorporation of electroporation techniques contributed in direct transesterification of microbial lipids by increasing the efficiency of biodiesel production rate.

Keywords: biodiesel, electroporation, microbial lipids, transesterification

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Authors: Zhala Ahmad, Zainab Lazim, Haider Hamzah

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Bacterial resistance is a pressing global health issue, with multidrug-resistant (MDR), extensively drug-resistant (XDR), and pandrug-resistant (PDR) strains to pose a serious threat. In this context, researchers are investigating effective, safe, and affordable metabolites to combat these pathogens. This study focuses on gum essential oil (GEO) extracted from Pistacia atlantica and its activity and the mechanism of action against XDR Gram-negative Acinetobacter baumannii. GEO was extracted by hydrodistillation and analyzed using GC-MS. Eleven A. baumannii isolates were collected from the ward environment of Burn and Plastic Surgery Hospital in Al Sulaymaniyah City, Iraq. They were identified using the VITEK 2 system, 16S rRNA gene, and confirmed with the blaₒₓₐ₋₅₁ gene; A. baumannii ATCC 19606 was used as a reference strain. The isolates were identified as resistant to twelve different antibiotics spanning six distinct antibiotic classes while showing susceptibility to tetracycline and trimethoprim. Over 40 chemical constituents were detected in the gum's essential oils, with α-pinene being the most abundant. GEO was found to inhibit the growth of A. baumannii isolates; the minimum inhibitory concentration (MIC) of GEO was 2.5 µl/ml. GEO induced protein leakage, phosphate, and potassium ion efflux, distorted cell morphology, and cell death in the tested bacteria. GEO exhibited bacterial clearance and anti-adhesion activity using Band-Aids. This study's findings suggest that GEO could be used as a potential alternative treatment for infectious diseases caused by XRD pathogens, shedding further light on the importance of GEO in biomedical applications. Future studies must focus on generating clinically feasible sources of GEO for testing in small animal models before proceeding to human trials, ensuring safe and effective translation from the laboratory to the clinic.

Keywords: antibiotic resistance, Acinetobacter baumannii, essential oils, Pistacia atlantica, alpha-pinene

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Authors: Thomas Monahan, Nicolas Gorius, Thanh Nguyen

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Exoplanet atmospheric parameters retrieval is a complex, computationally intensive, inverse modeling problem in which an exoplanet’s atmospheric composition is extracted from an observed spectrum. Traditional Bayesian sampling methods require extensive time and computation, involving algorithms that compare large numbers of known atmospheric models to the input spectral data. Runtimes are directly proportional to the number of parameters under consideration. These increased power and runtime requirements are difficult to accommodate in space missions where model size, speed, and power consumption are of particular importance. The use of traditional Bayesian sampling methods, therefore, compromise model complexity or sampling accuracy. The Atmospheric Retrievals conditional Generative Adversarial Network (ARcGAN) is a deep convolutional generative adversarial network that improves on the previous model’s speed and accuracy. We demonstrate the efficacy of artificial intelligence to quickly and reliably predict atmospheric parameters and present it as a viable alternative to slow and computationally heavy Bayesian methods. In addition to its broad applicability across instruments and planetary types, ARcGAN has been designed to function on low power application-specific integrated circuits. The application of edge computing to atmospheric retrievals allows for real or near-real-time quantification of atmospheric constituents at the instrument level. Additionally, edge computing provides both high-performance and power-efficient computing for AI applications, both of which are critical for space missions. With the edge computing chip implementation, ArcGAN serves as a strong basis for the development of a similar machine-learning algorithm to reduce the downlinked data volume from the Compact Ultraviolet to Visible Imaging Spectrometer (CUVIS) onboard the DAVINCI mission to Venus.

Keywords: deep learning, generative adversarial network, edge computing, atmospheric parameters retrieval

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Authors: Wan-Ting Kuo, Yi-Wen Liu, Hsiao-Sheng Liu

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Annual incidence of bladder cancer increases in the world and occurs frequently in the male. Most common type is transitional cell carcinoma (TCC) which is treated by transurethral resection followed by intravesical administration of agents. In clinical treatment of bladder cancer, chemotherapeutic drugs-induced apoptosis is always used in patients. However, cancers usually develop resistance to chemotherapeutic drugs and often lead to aggressive tumors with worse clinical outcomes. Approximate 70% TCC recurs and 30% recurrent tumors progress to high-grade invasive tumors, indicating that new therapeutic agents are urgently needed to improve the successful rate of overall treatment. Nonapoptotic program cell death may assist to overcome worse clinical outcomes. Autophagy which is one of the nonapoptotic pathways provides another option for bladder cancer patients. Autophagy is reported as a potent anticancer therapy in some cancers. First of all, we established a mouse orthotopic bladder tumor formation model in order to create a similar tumor microenvironment. IVIS system and micro-ultrasound were utilized to noninvasively monitor tumor formation. In addition, we carried out intravesical treatment in our animal model to be consistent with human clinical treatment. In our study, we carried out intravesical instillation of the autophagy inducer in mouse orthotopic bladder tumor to observe tumor formation by noninvasive IVIS system and micro-ultrasound. Our results showed that bladder tumor formation is suppressed by the autophagy inducer, and there are no significant side effects in the physiology of mice. Furthermore, the autophagy inducer upregulated autophagy in bladder tissues of the treated mice was confirmed by Western blot, immunohistochemistry, and immunofluorescence. In conclusion, we reveal that a novel autophagy inducer with low side effects suppresses bladder tumor formation in our mouse orthotopic bladder tumor model, and it provides another therapeutic approach in bladder cancer patients.

Keywords: bladder cancer, transitional cell carcinoma, orthotopic bladder tumor formation model, autophagy

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Authors: Priyanka Yadav, Rajkumar Ghosh, Alok Saini

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Human civilization cannot exist and thrive in the absence of adequate water. As a result, even in smart cities, water plays an important role in human existence. The key causes of this catastrophic water scarcity crisis are lifestyle changes, over-exploitation of groundwater, water over usage, rapid urbanization, and uncontrolled population growth. Furthermore, salty water seeps into deeper aquifers, causing land subsidence. The purpose of this study on artificial groundwater recharge is to address the water shortage in Gomti Nagar, Lucknow. Submersibles are the most common methods of collecting freshwater from groundwater in Gomti Nagar neighbourhood of Lucknow. Gomti Nagar area has a groundwater depletion rate of 1968 m3/day/km2 and is categorized as Zone-A (very high levels) based on the existing groundwater abstraction pattern - A to D. Harvesting rainwater using roof top rainwater harvesting systems (RTRWHs) is an effective method for reducing aquifer depletion in a sustainable water management system. Rainwater collecting using roof top rainwater harvesting systems (RTRWHs) is an effective method for reducing aquifer depletion in a sustainable water conservation system. Due to a water imbalance of 24519 ML/yr, the Gomti Nagar region is facing severe groundwater depletion. According to the Lucknow Development Authority (LDA), the impact of installed RTRWHs (plot area 300 sq. m.) is 0.04 percent of rainfall collected through RTRWHs in Gomti Nagar region of Lucknow. When RTRWHs are deployed in all buildings, their influence will be greater. Bye-laws in India have mandated the installation of RTRWHs on plots greater than 300 sq.m. A better India without any water problem is a pipe dream that may be realized by installing residential and commercial rooftop rainwater collecting systems in every structure. According to the current study, RTRWHs should be used as an alternate source of water to bridge the gap between groundwater recharge and extraction in smart city viz. Gomti Nagar, Lucknow, India.

Keywords: groundwater recharge, RTRWHs, harvested rainwater, rainfall, water extraction

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Authors: C. Miranda, R. Soares, S. Cunha, L. Ferreira, G. Igrejas, P. Poeta

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Different animal species, including ornamental animals, are reported as potential reservoirs of antibiotic resistance genes. Consequently, these resistances can be disseminated in the environment and transferred to humans. Moreover, multidrug-resistant bacteria reduce the efficacy of antibiotics, as the case of vancomycin-resistant enterococci. Enterococcus faecalis and E. faecium are described as the main nosocomial pathogens. In this line, the aim of this study was to characterize resistance and virulence genes of enterococci species isolated from samples of food supplied to ornamental animals during 2020. The 29 enterococci isolates (10 E. faecalis and 19 E. faecium) were tested for the presence of the resistance genes for the following antibiotics: erythromicyn (ermA, ermB and ermC), tetracycline (tetL, tetM, tetK and tetO), quinupristin/dalfopristin (vatD and vatE), gentamicin (aac(6’)-aph(2’’)-Ia), chloramphenicol (catA), streptomycin (ant(6)-Ia) and vancomycin (vanA and vanB). The same isolates were also tested for 10 virulence factors genes (esp, ace, gelE, agg, fsr, cpd, cylA, cylB, cylM and cylLL). The resistance and virulence genes were performed by PCR, using specific primers and conditions. Negative and positive controls were used in all PCR assays. The most prevalent resistance genes detected in both enterococci species were ermB (n=15, 52%), ermC (n=7, 24%), tetK (n=8, 28%) and vatE (n=4, 14%). Resistance genes for vancomycin were found in ten (34%) E. faecalis and ten (34%) E. faecium isolates. Only E. faecium isolates showed the presence of ermA (n=2, 7%), tetL (n=13, 45%) and ant(6)-Ia gene (n=4, 14%). A total of nine (31%) enterococci isolates were classified as multidrug-resistant bacteria (3 E. faecalis and 6 E. faecium). In three E. faecalis and one E. faecium were not detected resistance genes. The virulence genes detected in both species were agg (n=6, 21%) and cylLL (n=11, 38%). In general, each isolate showed only one of these virulence genes. Five E. faecalis and eleven E. faecium isolates were negative for all analyzed virulence genes. These preliminary results showed the presence of multidrug-resistant enterococci in food supplied to ornamental animals, in particular vancomycin-resistant enterococci. This genotypic characterization reinforces the relevance to public health in the control of antibiotic-resistant bacteria.

Keywords: antibiotic resistance, enterococci, feed, ornamental animals

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Authors: Muhammad Adeel Arshad, Shaukat Ali Bhatti, Faiz-ul Hassan

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Manipulating microbial ecosystem in the rumen is considered as an important strategy to optimize production efficiency in ruminants. In the past, antibiotics and synthetic chemical compounds have been used for the manipulation of rumen fermentation. However, since the non-therapeutic use of antibiotics has been banned, efforts are being focused to search out safe alternative products. In tropics, crop residues and forage grazing are major dietary sources for ruminants. Poor digestibility and utilization of these feedstuffs by animals is a limiting factor to exploit the full potential of ruminants in this area. Hence, there is a need to enhance the utilization of these available feeding resources. One of the potential strategies in this regard is the use of direct-fed microbes. Bacteria and fungi are mostly used as direct-fed microbes to improve animal health and productivity. Commonly used bacterial species include lactic acid-producing and utilizing bacteria (Lactobacillus, Streptococcus, Enterococcus, Bifidobacterium, and Bacillus) and fungal species of yeast are Saccharomyces and Aspergillus. Direct-fed microbes modulate microbial balance in the gastrointestinal tract through the competitive exclusion of pathogenic species and favoring beneficial microbes. Improvement in weight gain and feed efficiency has been observed as a result of feeding direct-fed bacteria. The use of fungi as a direct-fed microbe may prevent excessive production of lactate and harmful oxygen in the rumen leading to better feed digestibility. However, the mechanistic mode of action for bacterial or fungal direct-fed microbes has not been established yet. Various reports have confirmed an increase in dry matter intake, milk yield, and milk contents in response to the administration of direct-fed microbes. However, the application of a direct-fed microbe has shown variable responses mainly attributed to dosages and strains of microbes. Nonetheless, it is concluded that the inclusion of direct-fed microbes may mediate the rumen ecosystem to manage lactic acid production and utilization in both clinical and sub-acute rumen acidosis.

Keywords: microbes, roughages, rumen, feed efficiency, production, fermentation

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Authors: Yasamin Rahimi, Ali Kamandi, Abbas Hoseini, Hesam Haddad

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Online/offline chat is a convenient approach in the electronic markets of second-hand products in which potential customers would like to have more information about the products to fill the information gap between buyers and sellers. Online peer in peer market is trying to create artificial intelligence-based systems that help customers ask more informative questions in an easier way. In this article, we introduce a method for the question/answer system that we have developed for the top-ranked electronic market in Iran called Divar. When it comes to secondhand products, incomplete product information in a purchase will result in loss to the buyer. One way to balance buyer and seller information of a product is to help the buyer ask more informative questions when purchasing. Also, the short time to start and achieve the desired result of the conversation was one of our main goals, which was achieved according to A/B tests results. In this paper, we propose and evaluate a method for suggesting questions and answers in the messaging platform of the e-commerce website Divar. Creating such systems is to help users gather knowledge about the product easier and faster, All from the Divar database. We collected a dataset of around 2 million messages in Persian colloquial language, and for each category of product, we gathered 500K messages, of which only 2K were Tagged, and semi-supervised methods were used. In order to publish the proposed model to production, it is required to be fast enough to process 10 million messages daily on CPU processors. In order to reach that speed, in many subtasks, faster and simplistic models are preferred over deep neural models. The proposed method, which requires only a small amount of labeled data, is currently used in Divar production on CPU processors, and 15% of buyers and seller’s messages in conversations is directly chosen from our model output, and more than 27% of buyers have used this model suggestions in at least one daily conversation.

Keywords: smart reply, spell checker, information retrieval, intent detection, question answering

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Authors: Mane Darbinyan, Lusine Hayrapetyan, Elen Matevosyan

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Artificial Intelligence in Education (AIED) has been created to help students get ready for the workforce, and over the past 25 years, it has grown significantly, offering a variety of technologies to support academic, institutional, and administrative services. However, this is still challenging, especially considering the labor market's rapid change. While choosing a career, people face various obstacles because they do not take into consideration their own preferences, which might lead to many other problems like shifting jobs, work stress, occupational infirmity, reduced productivity, and manual error. Besides preferences, people should properly evaluate their technical and non-technical skills, as well as their personalities. Professional counseling has become a difficult undertaking for counselors due to the wide range of career choices brought on by changing technological trends. It is necessary to close this gap by utilizing technology that makes sophisticated predictions about a person's career goals based on their personality. Hence, there is a need to create an automated model that would help in decision-making based on user inputs. Improving career guidance can be achieved by embedding machine learning into the career consulting ecosystem. There are various systems of career guidance that work based on the same logic, such as the classification of applicants, matching applications with appropriate departments or jobs, making predictions, and providing suitable recommendations. Methodologies like KNN, Neural Networks, K-means clustering, D-Tree, and many other advanced algorithms are applied in the fields of data and compute some data, which is helpful to predict the right careers. Besides helping users with their career choice, these systems provide numerous opportunities which are very useful while making this hard decision. They help the candidate to recognize where he/she specifically lacks sufficient skills so that the candidate can improve those skills. They are also capable to offer an e-learning platform, taking into account the user's lack of knowledge. Furthermore, users can be provided with details on a particular job, such as the abilities required to excel in that industry.

Keywords: career guidance system, machine learning, career prediction, predictive decision, data mining, technical and non-technical skills

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Authors: Aoxue Yang, Weili Tian, Yonghe Wu, Haikun Liu

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Brain tumor stem cells (BTSCs) are resistant to therapy and give rise to recurrent tumors. These rare and elusive cells are likely to disseminate during cancer progression, and some may enter dormancy, remaining viable but not increasing. The identification of dormant BTSCs is thus necessary to design effective therapies for glioblastoma (GBM) patients. Little progress has been made in therapeutic treatment of glioblastoma in the last decade despite rapid progress in molecular understanding of brain tumors1. Here we show that the stress hormone glucocorticoid is essential for the maintenance of brain tumor stem cells (BTSCs), which are resistant to conventional therapy. The glucocorticoid receptor (GR) regulates metabolic plasticity and chemoresistance of the dormant BTSC via controlling expression of GPD1 (glycerol-3-phosphate dehydrogenase 1), which is an essential regulator of lipid metabolism in BTSCs. Genomic, lipidomic and cellular analysis confirm that GR/GPD1 regulation is essential for BTSCs metabolic plasticity and survival. We further demonstrate that the GR agonist dexamethasone (DEXA), which is commonly used to control edema in glioblastoma, abolishes the effect of chemotherapy drug temozolomide (TMZ) by upregulating GPD1 and thus promoting tumor cell dormancy in vivo, this provides a mechanistic explanation and thus settle the long-standing debate of usage of steroid in brain tumor patient edema control. Pharmacological inhibition of GR/GPD1 pathway disrupts metabolic plasticity of BTSCs and prolong animal survival, which is superior to standard chemotherapy. Patient case study shows that GR antagonist mifepristone blocks tumor progression and leads to symptomatic improvement. This study identifies an important mechanism regulating cancer stem cell dormancy and provides a new opportunity for glioblastoma treatment.

Keywords: cancer stem cell, dormancy, glioblastoma, glycerol-3-phosphate dehydrogenase 1, glucocorticoid receptor, dexamethasone, RNA-sequencing, phosphoglycerides.

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