Miracle-dz/UniFAR-FTUs huggingface dataset:
Phenotypic and genetic characteristics of fecundity in sheep. A review

Ivanova, T. , Stoikova-Grigorova, R. , Bozhilova-Sakova, M. , Ignatova, M. , Dimitrova, I. & Koutev, V. (2021). Phenotypic and genetic characteristics of fecundity in sheep. A review. Bulg. J. Agri. Sci., 27 (5), 1002–1008 The phenotypic characteristics of animals are result of the complex interaction of a number of genetic and non-genetic factors, which usually act simultaneously and it is difficult to determine the degree of influence of each of them. Early identification of the genetic traits of individuals enables more efficient management of selection. Fertility determins the cost-effectiveness of sheep farming, regardless of productive direction. The individual fertility of the animals is determined by the number of lambs born per sheep. This trait is characterized by a low inheritance rate, hence conventional breeding methods shows slow progress. The introduction of new molecular-based technologies to improve productivity contributes to a greater and faster effect on the realization of animal genetic resources. The assessment of the breeding value of animals at the earliest possible age makes it possible to maximize the effect of the selection and to increase the use of animals with the highest genetic potential. The molecular markers and the application of RFLP-PCR method allow the determination of allelic variants of genes related to the quantity and quality of animal productivity. By identifying the different polymorphic variations and their phenotypic manifestation, a database can be accumulated to manage the genetic progression of economically important traits. Many mutations have been found in sheep that affect fertility and ovulation rates to varying degrees. Large number of mutations which affects ovulation have been found in genes expressing different proteins, such as the BMPR1B or FecB (Booroola gene or the bone morphogenetic protein receptor type 1B), GDF9 or FecG (the growth differentiation factor 9b) and BMP15 or FecX (a bone morphogenetic protein 15).
Industrie aérospatiale nord-américaine et performance des sous-traitants: Écarts entre le Canada et les États-Unis

The aerospace industry is most challenging for small and medium enterprises (SMEs) which are involved as subcontractors. New conditions such as globalization and technology-led competition bring about major changes in terms of which capabilities are required to sustain corporate growth. This paper offers an overview of a survey conducted in North America where 273 SMEs from Canada and the United States were evaluated and compared. Results indicate significant differences between the two countries, and particularly for the medium-sized firms. Canadian subcontractors tend to0501ntain a traditional profile whereas their American counterparts are clearly more proactive, both from a technological and organizational perspective. In view of the Canadian major firms' success on international markets, these results raise questions about the capacity of the Canadian supplier base to participate in building and reinforcing this success. L'industrie aerospatiale presente des defis importants pour les petites et moyennes entreprises (PME) impliquees a titre de sous-traitants. La predominance des facteurs technologiques et de la concurrence internationale impose le developpement d'une gamme elargie de competences. Cet article presente les resultats d'une recherche empirique visant a identifier ces competences. Les donnees sont tirees d'une enquete realisee aupres de 273 PME localisees sur le territoire nord-americain (Canada et Etats-Unis), et impliquees dans ce secteur. Les resultats montrent des ecarts importants entre les firmes des deux pays, plus particulierement du cote des firmes de taille moyenne. Les PME canadiennes s'ecartent peu du profil de sous-traitant traditionnel, alors que les firmes americaines affichent un comportement nettement plus proactif, autant sur le plan organisationnel que technologique. Etant donne le succes recent de plusieurs donneurs d'ordres canadiens sur les marches etrangers, les resultats de cette etude soulevent de nombreuses interrogations sur la capacite des firmes sous-traitantes a contribuer a ce succes.
A high-throughput, automated, cell-free expression and screening platform for antibody discovery

Antibody discovery is bottlenecked by the individual expression and evaluation of antigen-specific hits. Here, we address this gap by developing an automated workflow combining cell-free DNA template generation, protein synthesis, and high-throughput binding measurements of antibody fragments in a process that takes hours rather than weeks. We apply this workflow to 119 published SARS-CoV-2 neutralizing antibodies and demonstrate rapid identification of the most potent antibody candidates.
IOT BASED CIVIL STRUCTURAL HEALTH MONITORING SYSTEM

: The early stage detection of damage and prediction of an upcoming accident in civil structure require continuous structural health monitoring for the large area. The position of sensors and monitoring system also plays an important role in structural monitoring which increases demand for the reliable civil structural monitoring system. On the other hand, determining the dynamic behavior of civil structure require the dense development of sensor. The wired civil structure monitoring system is highly expansive and always needs large installation space to deploy. This project describes wireless sensor network which consumes low power and less space. The wireless sensor network is developed to detect physical parameters of civil structures continuously and send the sensor information to internet cloud server via TCP/IP protocol. The user can access graphical view of various sensors from the cloud server. The cloud server utilizes MATLAB program to give the graphical representation of WSN data. The WSN consists of a sensor to continuously sense various physical parameters of a Civil structure such as temperature, humidity, light
FACTORS AFFECTING TEACHERS PERCEPTION OF E-LEARNING: A REVIEW OF THE LITERATURE

The growing interest in E-learning seems to be coming from different directions like corporate and educational sectors. Corporate sees E-learning as a tool to save cost in terms of training and travelling to the learning centre (Bassi.2010), as from the educational point of view, it is an additional access to improving the teaching and learning process and to enhance a better communication between the teachers and learners. This article reviews personal, institutional, technological and other factors that affect teachers’ perception of E-Learning, since we know that teachers’ perceptions have an impact on their teaching practices. The article concludes there are numerous factors that influence teachers’ perceptions of E-Learning. Teachers ‘feelings, knowledge and attitudes influence their use of e-learning in teaching. Finally, factors (barriers) that discourage the use of e-learning by teachers were also reviewed in this article. KEYWORDSPerception, E-Learning; Personal, institutional and technological factors.
Identifying and exploiting tolerance to unexpected jumps in synthesized strategies for GR(1) speciﬁcations

—When used as part of a hybrid controller, ﬁnite-memory strategies synthesized from LTL speciﬁcations rely on an accurate dynamics model in order to ensure correctness of trajectories. In the presence of uncertainty about this underlying model, there may exist unexpected trajectories that manifest as unexpected transitions under control of the strategy. While some disturbances can be captured by augmenting the dynamics model, such approaches may be conservative in that bisimulations may fail to exist for which strategies can be synthesized. In this paper, we characterize the tolerance of such hybrid controllers - synthesized for generalized reactivity(1) speciﬁcations-to disturbances that appear as unexpected jumps (transitions) to states in the discrete strategy part of the controller. As a ﬁrst step, we show robustness to certain unexpected transitions that occur in a ﬁnite-manner, i.e., despite a certain number of unexpected jumps, the sequence of states obtained will still meet a stricter speciﬁcation and hence the original speciﬁcation. Additionally, we propose algorithms to improve robustness by increasing tolerance to additional disturbances. A robot gridworld example is presented to demonstrate the application of the developed ideas and also to obtain empirical computational and memory cost estimates.
PII: S0967-070X(00)00035-4

This article reviews major events and trends in metropolitan transportation planning and policy during the 1990s in three divergent Paci®c rim jurisdictions: New Zealand, Chile, and California. Major metropolitan areas in each country have seen rising motorization, increasing congestion, and privatization of transportation services. Devolution of transportation planning responsibility has occurred; to a lesser degree, funding responsibility has been devolved from central to regional/local government. New Zealand pushed privatization harder in the 1990s than either Chile or California. While no dominant model of transportation planning has emerged, metropolitan-level planning has become more prominent and autonomous in each country studied. q 2001 Elsevier Science Ltd. All rights reserved.
Human Action Recognition with Expandable Graphical Models

Human motion analysis has attracted increasing attention in the past decade due to its scientific challenges and social and economic significance in a wide range of applications including video surveillance for home, workplace and public environment, human computer interface (HCI), study and diagnosis of movement disorder, tele-monitoring of patients and elderly people and sports training. This problem has been addressed mainly from two aspects: kinetics and kinematics. Kinetics studies the forces and torques that generate the movement. ABStrAct
ARTIFICIAL INTELLIGENCE: THE NEW AGE OF CYBERSECURITY

Technology has come a long way with rapid advancements on the Internet, IoT (Internet of Things), and other such connecting Technologies. Currently, scientists and experts alike, are facing many issues to prevent cyber-attacks and data breaches. Corporate enterprises and individuals are more connected than ever before, thus leading to high amounts of network traffic. As a result, detecting and preventing security attacks is getting more and more difficult to be handled by us humans alone. Hence, Artificially Intelligent Software models could be developed to defend against such cyber-attacks and therefore, can also improve cybersecurity using such strategies. This paper discusses the implementations and some plausible areas where AI can be implemented in the field of Cybersecurity. Index Terms Artificial Intelligence, Cyber-Security, Expert System, Intelligent Agent, Neural Nets, Constraint Tackling.
Increasing Driver Flexibility through Personalized Menus and Incentives in Ridesharing and Crowdsourced Delivery Platforms

: Allowing drivers to choose which requests to fulﬁll provides drivers with much-needed autonomy in ridesharing and crowdsourced delivery platforms. While stochastic, a driver’s acceptance of requests in their menu is inﬂuenced by the platform’s offered compensation. Therefore, in this work, we create and solve an optimization model to determine personalized menus and incentives to offer drivers. We exploit variable properties to circumvent nonlinear variable relationships, formulating the model as a linear integer program. Stochastic driver responses are modeled as a sample of variable and ﬁxed scenarios. An imposed premium counterbalances solution overﬁtting. Solution methods decompose and iterate, improving performance of computational experiments that use request/driver trip information from the Chicago Regional Transportation Network. Our approach outperforms alternative methods and a ﬁxed incentives menu-only model by strategically using personalized incentives to prioritize promising matches and increase drivers’ willingness to accept requests. This beneﬁts both customers and drivers: the average driver income is increased by 4.1% compared to the menu-only model, and 96.6% of requests are matched (4.1% higher than the menu-only method). Higher incentives are offered when drivers are more likely to accept, while fewer incentives and menu slots are reserved for driver-request pairs less likely to be accepted.
CONTENT BASED IMAGE RETRIEVAL USING HUMAN INTERACTION (RF) WITH AUDITING SCHEME IN CLOUD COMPUTING ENVIRONMENT

—CBIR is the mainframe of Image Retrieval System. To understand query semantics and users expectations so as to communicate faithful results in terms of accuracy, Relevance Feedback is incorporated into CBIR System. This system allows users to progressively refine the search results, to access iteratively the results as “relevant/irrelevant” or even giving him/her the opportunity to specify a degree of relevance, the system creates a new query that better captures the user’s needs, hence raising the opportunity to get more relevant image results. In the watermark-based protocol, a unique watermark is directly embedded into the encrypted images by the cloud server before images are sent to the query user. Hence, when an illegal image copy is found, the unlawful query user who distributes the image can be traced by the watermark extraction. Feature vectors get protected by the secure hashing algorithm, auditing and alert generation are used at image users side for verification purpose. TPA (Third Party Auditor) is used to detect fraud or malicious activities performed in a cloud environment.
Texting to Save Lives: Evidence from Cardiovascular Treatment Reform in Mexico*

Can widely available technologies be leveraged to reduce healthcare fragmentation in a costeffective way? I evaluate a program implemented by the largest public healthcare provider in Mexico (IMSS) to reduce heart attack mortality by minimizing the time to treatment for patients. The program improves within-hospital capabilities and increases across-hospital transfer coordination through a set of group chats, most commonly on WhatsApp, that substantially improved the ability of physicians in each hospital network to communicate with one another on transfer decisions. I first document a large effect among hospitals that have a higher survival gap relative to the specialized centers they send patients to: survival rates increase by 29% (12 percentage points) and transfers by 85% (5 percentage points). I then present a model that disentangles the capabilities and communication channels and allows me to link the reduced-form results to structural parameters. A counterfactual policy analysis shows that the chat groups are responsible for 68% of the survival effect and that, without the improvements in capabilities, transfers would have been substantially higher. Additional exercises highlight a degree of substitution between both components and, through a welfare framework, large returns to utilizing widely available technology. This paper is updated frequently. The latest version can be found here. *I am immensely grateful to my advisors Jonathan Gruber, Joseph Doyle, John Van Reenen and Abhijit Banerjee for their enthusiasm and guidance. I thank David Autor, Amy Finkelstein, Ben Olken, Jim Poterba and Frank Schilbach for their useful comments on the project as well as participants in the development, organizational and PF lunches at MIT for useful questions and discussions. I am grateful to Kensuke Teshima and Hitoshi Shigeoka for their contributions on earlier stages of the project as well as Christian Norton and Kevin Schmidt for their collaboration. I am especially grateful to Dr. Gabriela Borrayo for her willingness and openness to discuss the Codigo Infarto program in detail. aribro@mit.edu
DESIGN A FFT AND VERIFY USING RAZOR FLIP FLOP RAM SETS

: Basically, cryptographic algorithms consists of large integers like RSA and Diffie-hellman. This algorithm performs mostly time consuming operations like modular multiplication operation. The implementation of modular multiplication function takes more than 75 percent of time within in the RSA for more than 1024-bit moduli. Here fast multiplier architectures are used to minimize the delay and increase the throughput using parallelism and pipelining. But this architectures occupy large area and gives less efficiency. In this paper it consists of integration of fast Fourier transform method into the framework and as well as it produces improved FFT-based Montgomery modular multiplication (MMM) algorithm to obtain high area-time efficiency. In existed system zero padding operation is performed to compute the modular multiplication steps directly using cyclic and nega cyclic convolutions. Now to reduce the convolution length by half in the number weighted theoretic algorithm, FFT algorithm is used which provide fast convolution computation. In proposed algorithm a general method is introduced for efficient parameter selection. In this proposed architecture single and double butterfly structures are designed to get low area-latency solutions and these are implemented on Xilinx Virtex-6 FPGAs. So
Fatigue Performance of Long-Term Aged Plastic Granule Modified Bitumen Containing Chemical Additives

Recently warm mix asphalt (WMA) technologies have been introduced to rubberized asphalt mixtures to decrease the required construction temperatures and alleviate hazardous gas emissions. Molten plastic asphalt pavements combining with WMA have the potential to improve long term pavement performance. This study aims to investigate the fatigue performance of modified bitumen with molten plastic (MP) containing warm mix additives using different characterization methods. The effects of molten plastic modifier (MP) content (5%, 10%, 15%, and 20% by weight of base bitumen) and warm mix additives on the binder fatigue performance were investigated. Various laboratory tests, including frequency sweep tests, time sweep (TS) tests and linear amplitude sweep (LAS) tests, were conducted on the long term aged binders to obtain indicators of fatigue performance. Results show that there is a good correlation between the measured fatigue life determined by TS tests using the dissipated energy concept and the predicted fatigue life determined by LAS tests using the simplified viscoelastic continuum damage (S VECD) theory. However, the traditional Superpave fatigue parameter and the G R parameter cannot characterize accurate enough the fatigue performance of modified binders. Modified binders exhibit superior fatigue performance compared to the neat bitumen. The effects of warm mix additives on the fatigue performance are different for neat bitumen compared to modify binder. Based on the findings in this study, rubberized asphalt mixture combining with WMA additives is expected to have a promising long term fatigue performance.
TITLE: EFFECTS OF LOGGING ON THE GROWTH OF JUVENILE COHO

approved: r. James 0. Hall The objective bY this research was to study the effects of increased water temperature characteristic of clearcut watersheds of Pacific coastal streams upon the growth rate of juvenile coho salmon. The natural temperature fluctuations of the stream were used in the study of growth of underyearling fish held in aquariums and fed at various consumption levels. Juvenile coho experiencing the cooler temperatures of the control stream demonstrated generally better growth rates than did those that experienced the warmer temperatures of the clearcut stream. The reduced maintenance requirements in the control experiment indicated a reduced basal metabolic demand, which allowed for a greater portion of the food consumed to be utilized for growth. This was particularly true at low levels of consumption. Growth rates of juvenile coho salmon in the wild state were found to be higher in the logged stream as compared to the unlogged stream. This difference from the experimental results is thought to be due to a change in availability and abundance of food. There was a marked Redacted for privacy decrease in the cutthroat trout population in the clearcut strearn,which may have reduced conetition for the coho salmon. Increased exposure of the stream to solar radiation also may. have permited en increase in primary production essentia' for small organisms upon which the juvenile coho feed. There was no apparent influence of infestation by salmon poisoning fluke on the condition of the juvenile coho. EFFECTS OF LOGGING ON THE GROWTH OF JUVENILE COHO SALMON
Impact of Retransmission on VoWiFi Cell Capacity Estimation using IEEE 802.11ax WiFi Standard

Wireless Fidelity (WiFi) is becoming more popular for its ability to provide cost-effective solutions to overcome call drops occurring in cellular networks due to poor signal strength. We focused on Voice over Internet Protocol (VoIP) over WiFi as Voice over WiFi (VoWiFi) in our study. We have developed analytical models incorporating Arbitration Inter-frame Spacing (AIFS) to boost the VoWiFi cell capacity of IEEE 802.11ax (i.e. sixth generation Wireless Local Area Network (WLAN) standard). Using DCF Inter-frame Spacing (DIFS) and AIFS, we have estimated VoWiFi cell capacity with/without Request To Send (RTS) and Clear To Send (CTS) frames for constant bit rate (CBR) traffic. Further, we have extended our models to support retransmission mechanism to prevent packet loss and compared results using DIFS and AIFS to determine their efficiency.
DESIGN AND IMPLEMENTATION OF SMART MONITORING SYSTEMS IN HOSPITAL WAGON USING IOT TECHNOLOGY

—This paper presents a wearable sensor network system for Internet of Things (IoT) connected safety and health applications. Safety and health of patients are important; therefore, an IoT network system which can monitor both environmental and physiological can greatly improve the life time of the patient. The wearable sensors on different subjects can communicate with each other and transmit the data to a gateway via a Local Area Network which forms a heterogeneous IoT platform with Wi-Fi based medical signal sensing network. It consists of two sections: the basic information and condition of patient is collected in the wagon by the means IoT (Internet of Things) and make it available to hospital before the emergency vehicle reaches the hospital. On the base of such data, the system is able to detect anomalous situations and provide information about the status directly and exclusively to the hospital. The second path is control of traffic lights from the wagon and makes free for its path automatically. This project is to save the time of major late time aspects in more efficient manner and save the life.
An approach for Fake news detection by using Deep learning technique

— The quick access to information on social media networks as well as its exponential rise also made it difficult to distinguish between fake information or real information. The fast dissemination by way of sharing has enhanced its falsification exponentially. It is also important for the credibility of social media networks to distribute fake information. It thus became a study challenge to automatically check for misstatement of information through its source, content, or publisher. This paper demonstrates an approach to the identification by the artificial intelligence of false statements made by public figures. As a software system, two algos are being applied and a series of data tested. The highest result obtained for binary (true or false) labeling is 99 percent. Python 3.6 is the simulation method used here.