Miracle-dz/UniFAR-FTUs huggingface dataset:
A Theorem on the Relationship between Companion Form and Observability for Linear Time Invariant Systems

Similarity transformations of linear systems of differential equations are briefly discussed. The companion form of a matrix and of the system is introduced as well as the fundamental control concept of observability. A condition for linear systems that guarantees the existence and uniqueness of a linear transformation that transforms the original system into a companion system is stated. The question is then raised: if there is no way to transform a given system into its companion form, is there at least a way to transform the system matrix into a companion form? The concluding theorem proves that the answer is yes, and furthermore any transformation matrix that will do so must be a full rank observability matrix of the system. This result holds for all systems whose matrix’s characteristic polynomial is equal to its minimal polynomial.
A novel p.K116Q SNP in the OLR1 gene and its relation to fecundity in Awassi ewes.

Sheep's fecundity is determined by both twinning rate and litter size, both influenced by several genes, one of which is the OLR1 (oxidized low-density lipoprotein receptor) gene. This study aimed to determine the genetic variation of the OLR1 gene affecting the fecundity traits of Awassi ewes. The genomic DNA from 114 ewes with a single progeny and 86 ewes with twins was extracted. Polymerase chain reaction (PCR) was used to amplify three fragments (334 bp, 291 bp, and 274 bp) (exon 3, exon 4, and exon 6) of the OLR1 gene. Two genotypes of 334-bp amplicons - CC and CA - were detected. In a sequence reaction, the novel mutation p.K116Q was discovered in CA genotypes. There was a highly significant (P ≤ 0.01) association between the single nucleotide polymorphism (SNP) and reproductive traits, in that ewes with the p.K116Q SNP had lower litter size, twinning rate, fecundity, and lambing percentages than ewes with the CC genotype. These observations imply that the missense p.K116Q variant has an adverse effect on the traits under study and show that p.K116Q SNP has a negative influence on fecundity traits in Awassi sheep. Based on the findings of this study, it is clear that ewes with the p.K116Q SNP are associated with reduced litter size and reduced fecundity traits for this population.
Secure Data Aggregation Aided by Privacy Preserving in Internet of Things

With the rapid development of Internet of Things (IoT), more and more wireless smart devices are widely deployed in its typical applications. These devices acquire numerous data, and their security transmission is a challenge issue due to the openness and broadcast nature of wireless network. Security data aggregation (SDA) plays a significant role in IoT which can not only protect the data privacy but also reduce the network traffic among smart devices. In this paper, a multiple application SDA (MASDA) mechanism is proposed and it can ensure the data confidentiality without losing the integrity of data transmission. Firstly, we discuss an improved homomorphic message authentication code (iHMAC) which can verify the integrity of sensing data and eliminate the injection of false data. Secondly, a multiple application elliptic curve cryptography mechanism (iECC) is described. We introduce multiple types of data simultaneous encryption into an elliptic curve encryption system. This encryption mechanism aggregates the encrypted sensing data and prevents the sensing from being tampered and leaked in relay nodes. Finally, MASDA is a multiple application mechanism and provide both the confidentiality and integrity compared with other SDA schemes. It fuses the sensing data of different applications in a single data packet, and the base station can recover them one-by-one. The security analysis and the simulation experiments verify that MASDA has better performances in terms of the security, the computation cost, the communication overhead, and the data accuracy.
Robot Interaction Control in Unstructured Space Environment for Space Exploration

This paper demonstrates the advantage of nonlinear bang-bang impact force control for exploration of planet surface. Nonlinear bang-bang impact force control can make a robot successfully achieve contact tasks in a seamless fashion without changing control algorithm or controller gains throughout all three modes: free space, transition and constrained motion. Experiments show that overall performance of nonlinear bang-bang impact force control is comparable to and better than existing impact control techniques which employ more complicated control strategy.
SPECIFICATION, DESIGN AND IMPLEMENTATION OF A NEW IDS BASED ON THE TWO DETECTION APPROACHES

An IDS is a tool which is used to improve the level of security. We present in this paper different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection) for securing web servers and applications by the Intrusion Detection System (IDS).
Social media disinformation and voting decisions during 2019 presidential elections in Nigeria

Social media spread disinformation due to their characteristic features of anonymity and ease of producing, accessing, forwarding, and replicating media contents. Although studies have analyzed the influence of disinformation on voter choices, little is known about the false information that went viral on social media during the 2019 Nigerian presidential elections and its influence on voting decisions. Accordingly, the study identified social media disinformation about Muhammadu Buhari (All Progressives Congress) and Atiku Abubakar (Peoples Democratic Party), and its influence on voting decisions. Content analysis of Twitter, Facebook and YouTube posts revealed 10 viral pieces of disinformation about the contestants. Although the messages looked authentic because of their attribution, they were tagged false by independent fact checkers and disclaimers. They were also ascribed as false by survey respondents. Despite their presence, the information had little influence on voting decisions. While Facebook is the most used social media platform (48.6%), Twitter (60%) is the core channel of political disinformation. Posts used multiple story formats and information sources to make claims appear real. A combination of text, video, and picture was used for the political messaging, with pictures accompanying most stories for emphasis and message authentication. Each news story had more than 2000 likes and shares, which has implications for the continuous spread of false information.
Influence of the Electric Field Distribution on the Optical Voltage Transformer

In the optical voltage transformer based on Pockels effect,the electric field distribution between two electrodes is very important to the measurement results.An optical voltage sensor based on the BGO crystal is investigated with the finite element method(FEM). The electric field distribution between the two electrodes in the case of longitudinal modulation and transversal modulation is simulated respectively.The influence of the electric field non-uniformity on the measurement is discussed.The simulated results show that in a non-uniform electric field,the calculated scale factor is different from the approximation obtained from the uniform electric field assumption,and the difference is determined by the degree of non-uniformity.In the case of non-uniform electric field,the scale factor is also changed by the position and angle of the input light,thus the stability is influenced.Meanwhile,it is also shown that with the same set-up,the longitudinal modulation is preferred over the transversal modulation,since the electric field around the symmetric axis in the longitudinal modulation is more uniform.The electric field used in the transversal modulation is disturbed by the fringe effect,which will degenerate the stability.
Dynamic removal function modeling of bonnet tool polishing on optics elements

The dwell time function of the bonnet tool polishing on optics elements is achieved based on static removal function in recent studies.But the polishing tool keeps moving during the process,it's necessary to do the research on dynamic removal function.The static and dynamic contact zone is acquired through finite element simulation analysis,and so is the contact pressure.Both of the contact zones are circle and the size of them are almost the same.The peak point of the dynamic contact pressure has an offset contrary to the direction of the tool movement compared to the static contact pressure.The dynamic contact pressure distribution function is deduced by using the least square method based on the theory that the static pressure distribution function is a modified Gaussian function.The device which can extract both the dynamic and static contact zone is set up to capture them on the condition of different offset.Then the simulation results are verified.The dynamic removal function is deduced and numerical simulated based on the forward simulation and experiment results.The removal rate of the dynamic removal function is smaller than the static removal function and its nadir has a deflection compared to the latter.
A Recognition Model for Lane Change Intention Based on Neural Network

Timely and accurate identification of driver’s intention is considered helpful to avoid collisions. Driving in an on-road traffic situation makes it much more difficult to recognize the driving intention because of dynamic and uncertain information. However, the intentions can be inferred by the driver’s behaviors as he prepares to execute an action. The current studies focus on classifying driving intentions into car-following and lane changing. Therefore, a lane change intention recognition method was proposed in this study. A total of 10 on-road experiments on freeways were conducted to acquire time headway, driver’s eye-motion data, steering angle and lane departure data. With these data, the typical features under free driving and lane change conditions were analyzed respectively. Back-Propagation Neural Networks method was applied in this study to achieve the driving intention classification function. The proposed model successfully recognized 95 intentions in 100 lane change behaviors. The recognition result of the model can fit the target output at a degree of 0.99. This model is useful for surrounding drivers to choose the safest route to avoid collisions in the vehicle-infrastructure technology.
Application of X-ray Computed Tomography to Verify Bond Failures Mechanism of Fiber-Reinforced Fine-Grain Concrete

This paper proposes the use of X-ray computed tomography (µCT, xCT) measurements together with finite element method (FEM) numerical modelling to assess bond failures mechanism of fiber-reinforced fine-grain concrete. Fiber-reinforced concrete is becoming popular for application in civil engineering structures. A dynamically developing topic related to concretes is the determination of bond characteristics. Nowadays, modern technologies allow inspecting the inside of the element without the need to damage its structure. This paper discusses the application of computed tomography in order to identify damage occurring in the structure of fiber-reinforced fine-grain concrete during bond failure tests. The publication is part of a larger study to determine the bonding properties of Ukrainian steel fibers in fine-grain concrete. The authors focused on the visual evaluation of sections obtained from tomographic data. Separately, the results of volumetric analysis were presented to quantitatively assess the changes occurring in the matrix structure. Finite element analysis is an addition to the substantive part and allows us to compare real damage areas with theoretical stress concentration areas. The result of the work is the identification of a path that allows verification of the locations where matrix destruction occurs.
Phytochemical characterization and anti-cancer properties of extract of Ephedra foeminea (Ephedraceae) aerial parts

Purpose: To evaluate the phytochemical profile of methanol extract of Ephedra foeminea and assess its anti-carcer effect on a large set of normal and cancerous cell lines. Methods: Extraction of air-dried powder of aerial parts of E. foeminea was carried out with methanol. The bioactive compounds in the extract were determined using gas chromatography/mass spectrometry (GC-MS). The anti-cancer effect of the extract was determined by 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide (MTT) assay against various types of normal and cancer cell lines. Serial concentrations of plant extract were used, ranging from 7.812 to1000 μg/mL. Doxorubicin (DOX) served as standard drug. The half-maximal concentration (IC50) values of the extract and DOX for each cell line were determined, and the selectivity index (SI) was computed. Results: Phytochemical analysis showed that the extract contained several bioactive compounds, including alkaloids, flavonoids, sterols and fatty acids. The hazardous ephedra alkaloids (ephedrine and pseudoephedrine) were absent in the plant extract. The extract showed significant anti-proliferative activity against cancer cell lines, when compared with the positive control, doxorubicin (p < 0.05). Selective and concentration-dependent cytotoxicity was exhibited in cancer cell lines of breast (MCF-7), lung (A549), colon (Caco-2), liver (HepG-2) and prostate (PC-3). Weak selectivity was produced in other cancer cell lines, i.e., human epithelioma (Hep-2) and cervical carcinoma (Hela). Interestingly, non-cancerous cells showed no or weak cytotoxicity. Conclusion: Ephedra foeminea exerts potential selectivity in anti-proliferative effect against some cancer cell lines. Thus, it is a promising drug source for the production of new and selective anti-cancer medicines.
An Efficient Smote-based Model for Dyslexia Prediction

: Dyslexia is a learning disability which causes difficulty in an individual to read, write and spell and do simple mathematical calculations. It affects almost 10% of the global population and detecting it early is paramount for its effective handling. There are many different methods to detect the risk of Dyslexia. Some of these methods are using assessment tools, handwriting recognition, expert psychological help and also using the eye movement data recorded while reading. One of the other convenient and easy ways of detecting risk of dyslexia is to make an individual participate in a simple game related to phonological awareness, syllabic awareness, auditory discrimination, lexical awareness, visual working memory, and many more and recording the observations. The proposed research work presents an effective way of predicing the risk of dyslexia with high accuracy and reliability. It uses a dataset made available from the kaggle repository to predict the risk of dyslexia using various machine learning algorithms. Also it is observed that the dataset has an unequal distribution of positive and negative cases and so the classification accuracy is compromised if used directly. The proposed research work uses three resampling techniques to reduce the imbalance in the dataset. The resampling techniques used are undersampling using near-miss algorithm, oversampling using SMOTE and ADASYN. After applying the undersampling near-miss algorithm, best accuracy was given by SVC classifier with the value of 81.63%. All the other classifiers used in the experiment produced accuracy in the range of 64% to 79.08%. After using the oversampling algorithm SMOTE, the classifiers produced very good results in the evaluation metrics of accuracy,CV score, F1 Score and recall. The maximum accuracy was given by RandomForest with a value of 96.37% and closely followed by XGBBoosting and GradientBoosting with an accuracy of 95.14%. Decision tree, SVC and ADABoost got an accuracy of 91.26%, 93.36% and 93.48% respectively. Even the values of CV score, F1 and recall were considerably high for all these classifiers. After applying the oversampling technique of ADASYN, RandomForest algorithm generated maximum accuracy of 96.25%. Between the two oversampling techniques, SMOTE algorithm performed slightly better in producing better evaluation metrics than ADASYN. The proposed system has very high reliability and so can be effectively used for detecting the risk of dyslexia.
The Role of Technology Entrepreneurship Education in Encouraging to Launch New Ventures

Abstract Technology entrepreneurship refers to processes by which entrepreneurs use resources, and technical systems through collaborative exploration and experimentation to pursue opportunities. The purpose of this study is to explore the role of technology entrepreneurship to increase the intention and motivation of engineering students to establish and manage sustainable new ventures and commercialization of technologies developed in university laboratories. Quantitative data were collected via a questionnaire-based by investigating whether engineering students have sufficient entrepreneurial skills to evaluate opportunity, developing new products, and recognizing potential market applications. Engineering students need to be able to exploit opportunities that rely on scientific and technical knowledge to create and capture value by launch new venture. Our important findings have a series of important practical implications for managers, engineering students, engineers, and scientists interested in encouraging economic growth. For example, technology entrepreneurship education increases the intention to start a business and stimulates the activities in a group setting and a network context because of increasing global competition based on agility, creativity and innovation. The findings of the study also provide practical implications suggest that increasing engineering students understanding and awareness of entrepreneurship lead to greater levels of interest in entrepreneurship careers.
Analog Control (Front-End) Design of RFID Tag in 0.35 μm CMOS Technology

The RFID (Radio Frequency Identification) can be defined as Automatic identification technology which uses radio- frequency electromagnetic fields to identify objects carrying tags when they come close to a machine reader. In this paper authors designed the analog part using frequency 13.56 MHz in the RFID tag, includes a rectifier, demodulator and modulator. The first part a method of rectifier cascade combines multiple cells to obtain voltage doublers which used source of voltage on other components, the second part we call demodulator. Demodulator uses two stage of comparator that detects bias negative voltage, and the last part modulation used Amplitude Shift Keying (ASK) modulation. In this paper using 0. 35μm CMOS technology to design RFID tag. The research goals purpose to design the analog part of the RFID tags are biased to function well as it should. Keywords-component; RFID; tag; 0. 35µm CMOS technology; 13.56 MHz
Assessment of Actual Weight, Perceived Weight and Desired Weight of Romanian School Children-Opinions and Practices of Children and Their Parents

Objective: Children and parental awareness regarding weight is linked to the development and management of overweight and obesity. The aim of this study is to assess the actual weight, perceived weight, and desired weight of Romanian school children. Methods: A cross-sectional study was conducted in 2019 in seven schools from two counties of Romania and included 880 pupils aged between 10 and 15 years old and 665 parents. We administrated confidential questionnaires to the participants, and we measured children’s weight and height during school activities. Results: A total of 61.0% of pupils had normal weight, 7.4% were underweight, and 31.6% were overweight or obese. A total of 66.7% of normal weight children, 56.5% of overweight children, and 40% of underweight children perceived their weight accurately. Regarding parents, a majority correctly appreciated the weight of their normal weight children and only a third appreciated correctly the body weight of their underweight and overweight children. Factors such as body mass index, gender, weight related behaviors, parents’ estimation about their children’s weight, discussions of weight topics inside family, and bullying, cyberbullying and exclusion from groups were associated with misperceptions. Conclusion: The study provides useful information for health education activities targeting both children and their parents regarding appropriate body weight management of children.
MRI-GUIDED OPTICAL SPECTROSCOPY OF CANCER IN VIVO

MRI guided spectroscopy of tissue has been shown in both animals and humans. The interrogation of tissue with diffuse NIR light allows transmission over 8-10 cm of tissue, and spectroscopy and image resolution which is governed by the MR image. This abstract reviews the hardware required and how image-guidance might be used to localize the optical spectroscopy. The implementation is demonstrated in human breast cancer imaging, with full breast field of view, and demonstrates the ability to quantify haemoglobin levels in centimeter sized regions. When used in rodent imaging with injected fluorescent agents, image resolution can be millimeters in region size, and uptake and clearance of agents can be quantified. They key issue in this tracking of fluorescent molecular contrast agents it to identify the minimum region size and contrast level which is quantifiable reliably. However, once quantified, this paradigm allows molecular spectroscopy guided by MRI, and could allow receptor based imaging given appropriate contrast agents that are known to target to tumor-specific ligands. The use is reviewed, and the future potential discussed.
Antithrombotic Therapy Improves ICU Mortality of Septic Patients with Peripheral Vascular Disease

Objective The effectiveness of antithrombotic drugs for treating sepsis is controversial. Here, we explore the association between antithrombotic therapy and intensive care unit (ICU) mortality for septic patients with peripheral vascular disease. Methods This retrospective cohort study uses data from the Medical Information Mart for Intensive Care (MIMIC)-III database. Kaplan–Meier survival analyses were used to examine mortality among different groups. Cox regression and marginal structural Cox models (MSCMs) were used to adjust for confounding factors. Main Results. The final cohort from the MIMIC-III database included 776 patients, of which 701 survived and 75 perished. The anticoagulant (AC) group and the antiplatelet-anticoagulation (AC-AP) group survived better than the group without antithrombotic treatment (non-AT). The AC and AC-AP groups showed a 0.363-fold and 0.373-fold risk of ICU mortality, respectively, compared with the non-AT group when controlling for age, gender, CRRT, alcohol, heart failure, hypertension, diabetes, obesity, renal failure, liver disease, INR, PT, PPT, and SpO2. Antiplatelet therapy did not reduce ICU mortality. The same trends were apparent from the MSCM. In addition, the AC-AP group exhibited a lower risk of bleeding complications. Conclusion Although the antithrombotic group (AC and AC-AP groups) demonstrated a higher sequential organ failure assessment (SOFA) score than the group without antithrombotic treatment (non-AT group), the risk of ICU mortality was lower without increasing the risk of bleeding complications. Our study further suggested that anticoagulation therapy may benefit the prognosis of septic patients with peripheral vascular disease.