Miracle-dz/UniFAR-FTUs huggingface dataset:
A Paper on Cognitive Development in Children

The early cognitive performance of children born to mothers with epilepsy (n = 198) has been tested in this longitudinal analysis and compared to a group of children comprising the general population (n = 230). Children were evaluated using the Griffiths Mental Development Scales at a younger age than 2 years, either in their local participating hospital or in their home. An evaluator who was blinded to whether the mother of the boy had seizures as to the type of antiepileptic treatment performed the tests. Children exposed to sodium valproate had a statistically significant elevated risk of delayed early growth in contrast to the control children. Linear regression research revealed a statistically meaningful impact of sodium valproate toxicity on the child’s average developmental stage that was not compensated for by confounding variables. For children within an ad hoc group of less widely used antiepileptic medications, delayed early development is also observed, but conclusions should not be made because of the size of this group (n = 13). In children exposed to either carbamazepine or lamotrigine in utero, their overall developmental ability did not differ significantly. Differences observed in particular developmental areas for these two classes were not statistically important after the control for confounders such as social status and maternal IQ. Women with epilepsy should be aware of the dangers present to their future offspring prior to birth to allow for informed choices about treatment. Throughout infancy, infants subjected in utero to antiepileptic medications should be controlled to allow for early intervention if appropriate.
Motion models for multiple object tracking

In this paper, we consider the models for solving the problem of Multiple Object Tracking (MOT). We have compared the accuracy of the following models: autoregressive, moving average, Kalman filter. We compared the methods with using the MAPE metric and the 2dmot15 dataset. Prediction using an autoregressive model has good accuracy and can be used to build a MOT model.
Effects of Informatization Mind on Information Development Efforts and Academic Achievement of University Students Major in Sports

The purpose of this study is to identify the impact of informatization minds of college students majoring in sports on information development efforts and academic achievement. Accordingly, a survey was conducted on 200 college students majoring in physical education at D University, and 197 students were selected as the final effective samples. Data processing was conducted using SPSS 23 for frequency analysis, reliability analysis, correlation analysis, and regression analysis. The results are as follows: First, recognition of the necessity of informatization education, a subfactor of the informatization mind, has a positive impact on informatino development efforts. Second, recognition of the necessity of informatization education, understanding and utilization of informatization concepts among sub-factors of informatization minds have a positive impact on the major learning achievement. Third, all the conversational factors in the informatization mind have a positive impact on study problem resolution. Fourth, information development efforts have a positive impact on the major learning achievement and the study problem resolution. Therefore, efforts are needed to increase the information mindset of college students major in sports.
Change of Total Convergence on Visual Function Case after 3D Images

The level of change in distant PTC, near PTC, distant NTC, and near NTC was measured divided by before and after viewing 3D images. The 50 examinees were categorized into Low/ Middle/ High groups according to the level of change by test subject. Among all the entries, the exophoria group showed the highest change distribution, and in the distant and near NTC entries showed statistically significant differences in variation.
Adaptive Recommendation for Social Network Users with External Information

: Collaborative Filtering (CF) is a standout amongst the best suggestion approaches for overseeing data over-burden in reality. Ordinary CF strategies additionally treat all clients and components and neglect to recognize the assortment of client interests in various areas. This damages the truth that the interests of clients are constantly moved in some particular spaces, and clients who have comparative tastes in a single area may have totally unique tastes in another area. In this article, we propose Adaptive Domain sensitive Recommendation (ADsRec) algorithm, to make the rating expectation by all the while filtering the client component subgroup examination, in which a subset of client components is considered as a space of a client, a subset of components with comparable properties and a subset of clients who have interests in those components.
MERCILESS BORDER SECURITY SYSTEM

Our present day army does not include complete 360 degree surveillance thereby monitoring the entire border by soldiers alone is difficult due to various factors such as fog, snow, rain and other climatic conditions which would make visibility poor. Detection of bombs present underground is another major problem. Many harmful gases are being ejected that would make the soldiers drowsy which is making the enemies attack easily. The government is spending a huge amount of money in keeping the intruders in jail without merciless killing which is creating a loss. Thus our aim is to provide solutions for problems like 360 degree surveillance, Mine detection, Drug detection, Economical growth (GDP), Merciless killing, Surgical gas detection.
THE PROPER EMBEDDINGS OF LOKENTZIAN MANIFOLDS INTO A EUCLI»EAN(PSEUDO-EUCLlDEAN) BPACE BY SOLUTIONS OF THE D'ALEMBERTIAN EQtJATIONS

In [5J, I proved that any connected open Lorentzian manifold M can he topologically embedded into a euclidean (pseudo-euclidean) space by solutions of the d'Alembertian equation. This realizations of an abstract manifold is still not quite beautiful in some sence. For example, the figure 6 is topological embedding of a line into 2-dimensional euclidean space. However, it is not proper embedding of the line because of limit point of the line on one side. Thus it is desirable to get the proper embedding of our M for the purpose of applying the results to Mathematics and Physics. In this paper we will show that any globally hyperbolic connected open Lorentzian manifold can be properly embedded into a euclidean (pseudoeuclidean) space by solutions of the d' Alembertian equation on M.
Dimensional accuracy analysis of ABS based hip implants prepared by fused deposition modelling

Fused deposition modelling (FDM) is the most economical type of additive manufacturing (AM) technique. But, the poor surface texture and dimensional inaccuracy of FDM fabricated parts due to its fundamental working principle (layered manufacturing) limits the application domain of this technology. Researchers have successfully enhanced the surface finish of FDM based acrylonitrile butadiene styrene (ABS) replicas by treating them with hot or cold vapors of chemicals like acetone. However, the reflow of the material caused by such vapors inherently affect the other properties like dimensional accuracy, surface hardness and tensile strength. In this book chapter, researchers highlighted the dimensional accuracy of ABS replicas by integrating the FDM and vapor smoothing (VS) process. Taguchi L18 orthogonal array has been employed for optimizing the process parameters of combined process. The study highlighted that exposing ABS replicas to hot vapors of acetone resulted in dramatic improvement of surface finish with negligible variations in part dimensions. Keywords—Fused deposition modelling, Additive Manufacturing, Acrylonitrile butadiene styrene, Dimensional accuracy, Vapor smoothing
Vehicle Tracking and Controlling System Using GPS

:” The scale of theft of vehicles worldwide is worrying and the act needs to be curbed. Vehicle monitoring and controlling systems are different, with one or more disadvantages. Information and communication technologies (ICT) have positively succeeded in life by addressing many pressing problems to allow people to lead more easy lives. One such issue is automobile surveillance while parking or driving to ensure the safety of the vehicle and the people inside. This work suggests a tracking system for automobiles using wireless technology, including mobile phones, microcontrollers and GPS technology. An affordable and effective vehicle monitoring and safety mechanism using Global Positioning System (GPS) is developed in this paper. This system consists of a hardware device which is mounted in the car and a controlling unit cell phone to track the vehicle is used. The system receives feedback from the GPS satellites, sends this data via SMS to the designated user's phone with the assistance of the Global Mobile Communication System (GSM) module installed in the device. For presentation of graphical location information, the data sent to the control phone is processed and fed into a Geographic Information System (GIS) interface. ”
Spyware in the World of Computers

: In recent years, the word Spyware has become more and more popular. But the outline is still very indistinct. In this article it aims to clarify what Spyware is, the styles and ways it combines, and to investigate how it relates to other malware types. Take a closer look at a particular malicious "Spyware" case, and a variety of anti-Spyware programs. Finally, a list of tips on how to protect yourself from spyware attacks and how to become aware of spyware is compiled. The findings show that it is practically impossible to be completely secure against Spyware threats, and that none of Spyware's systems manage all forms of attacks. Many of them can however reduce the risk and increase the understanding of the risks. From the current analysis of the situation, it comes to the conclusion that Spyware is becoming a growing concern for businesses and end users, but still cannot overcome all the risks when developing anti-'spyware' tools.
Joint Exponential Smoothing and Trend-based Principal Component Analysis for Anomaly Detection in Wireless Sensor Networks

Principal Component Analysis (PCA) is a powerful technique in data analysis and widely used to detect anomalies in Wireless Sensor Networks. However, the performance of conventional PCA is not high on time-series data collected by sensors. In this paper, we propose a Joint Exponential Smoothing and Trend-based Principal Component Analysis (JES-TBPCA) for Anomaly Detection which is based on conventional PCA. Experimental results on a real dataset show a remarkably higher performance of JES-TBPCA comparing to conventional PCA model in detection of stuck-at and offset anomalies.
Interactive Web-based Simulations to Teach Econometrics: Making Abstract Concepts Tangible

We develop a series of publicly available interactive web-based modules and instructor materials to help students learn econometric concepts ranging from sampling distributions to omitted variable bias. The pedagogical literature supports using simulations to help students understand abstract statistical concepts but also cautions that ill-designed simulations may be ineffective. Most simulation tools currently available constrain users’ parameter choices, require excessive programming infrastructure, or lack real-world economics examples. Our modules allow students to experiment with inputs like sample size, number of replications, and underlying population distributions; students then see the impacts of their choices displayed visually in tables, histograms, and scatter plots. The modules can be used in classroom demonstrations or group activities in computer labs but also have sufficient instructions to allow independent exploration.
Soft-Tentacle Gripper for Pipe Crawling to Inspect Industrial Facilities Using UAVs

This paper presents a crawling mechanism using a soft-tentacle gripper integrated into an unmanned aerial vehicle for pipe inspection in industrial environments. The objective was to allow the aerial robot to perch and crawl along the pipe, minimizing the energy consumption, and allowing to perform contact inspection. This paper introduces the design of the soft limbs of the gripper and also the internal mechanism that allows movement along pipes. Several tests have been carried out to ensure the grasping capability on the pipe and the performance and reliability of the developed system. This paper shows the complete development of the system using additive manufacturing techniques and includes the results of experiments performed in realistic environments.
Albumin- Bilirubin (ALBI) Score a New and Simple Bedside Model to Predict Mortality in Patients with Cirrhosis

Aim: The existence of reliable prognostic indices is of paramount importance in the management of cirrhosis. The albumin-bilirubin (ALBI) score is a new model for assessing the severity of liver dysfunction. The aim of this study was to determine the ALBI score’s mortality prediction among cirrhotics and its comparison with MELD, CTP scores. Methods: This prospective study included one hundred cirrhotics where we calculated CTP, MELD and ALBI scores were calculated within 24 hours of admission. The mortality was assessed during the hospital stay and follow-up at 2, 4 and 6 months. The diagnostic accuracy of CTP, MELD and ALBI scores for mortality in cirrhotic patients was determined by receiver operating characteristic curve (ROC) analysis. Results: In the overall analysis, all of the three scores were significantly assess the mortality (CTP AUC=0.917, 95% CI: 0.857–0.977, P<0.0001; MELD AUC=0.935, 95% CI: 0.887–0.982, P<0.0001; ALBI AUC =0.964, 95% CI: 0.924–1.003, P<0.0001). The best cut-off values for CTP, MELD and ALBI were at >12.5 (sensitivity = 75.86%, specificity = 97.18%), >22.5 (sensitivity = 100%, specificity = 84.51%) and >-1.38 (sensitivity = 100%, specificity = 94.37%) with diagnostic accuracy of 91%, 89% and 96% respectively. Conclusion: The fact that ALBI score uses only two convenient parameters, readily obtained by easily accessible blood tests, objectively evaluated and being non inferior to CTP and MELD scores indicates that ALBI score might be a better mortality predictor in cirrhosis. Therefore, all these favour its applicability in clinical practice as a substitute for the CTP and MELD scores.
Developmental Regulation of Sirtuin Genes in Broiler Chicks

A family of enzymes known as sirtuins have related, yet unique metabolic functions and have been associated primarily with longevity and aging processes (Lombard et al., 2007). Evidence suggests that this family of enzymes including SIRT2, SIRT4, SIRT5, SIRT6, and SIRT7 is highly conserved across species (Greiss & Gartner, 2009). Despite wide study in species of yeast, flies, and mice, much less literature is available regarding these agingrelated proteins in poultry. The objectives of this study are three-fold. The first objective is to examine the expression of SIRT2, 4, 5, 6, and 7 in subcutaneous adipose tissue of developing broiler chicks at five age points, two pre-hatch and three post-hatch ages. The adipose tissue of embryonic ages was sampled at embryonic days 13, 15, and 17, and at days 7 and 14 after the chicks hatched. The second objective is to determine if and how expression of these six genes vary across the following three tissue types: subcutaneous adipose, liver, and abdominal adipose in post hatch chicks, at the same 7 and 14-day time points. Finally, this study will determine if there were any significant correlations between elevated gene expression and abundance of specific fatty acids subcutaneous fat samples. It was expected that expression levels would differ greatly from embryonic ages to post hatch time points, however, our data show that such expression changes were unique to each of sirtuin genes. Data collection for this study took place as part of a larger study under direction of the Voy Laboratory.
06 09 02 6 v 2 1 8 D ec 2 00 6 Fidelity , entanglement , and information complementarity relation

We investigate the dynamics of information in isolated multi-qubit systems. It is shown that information is in not only local form but also nonlocal form. We apply a measure of local information based on fidelity, and demonstrate that nonlocal information can be directly related to some appropriate well defined entanglement measures. Under general unitary transformations, local and nonlocal information will exhibit unambiguous complementary behavior with the total information conserved.
Introducing Fast and Secure Deterministic Stash Free Write Only Oblivious RAMs for Demand Paging in Keystone

Keystone is a trusted execution environment, based on RISC-V architecture. It divides the memory into a secure Keystone private memory and an unsecure non-Keystone memory, and allows code that lies inside the Keystone private memory to execute securely. Simple demand paging in Keystone ends up leaking sensitive access patterns of Keystone application to the Operating System(OS), that is assumed to be malicious. This is because, to access the unsecure non-Keystone memory, Keystone needs support of the OS. To mitigate this, Keystone needs to implement oblivious demand paging while obfuscating its page access patterns by using Oblivious RAM(ORAM) techniques. This causes substantial slowdown in the application execution. In this paper, we bridge the performance gap between application execution time with unsecure and secure demand paging in Keystone by using Deterministic, stash free, Write only ORAM (DetWoORAM) for oblivious demand paging. We also show why DetWoORAM, that is a write-only ORAM, is sufficient for oblivious demand paging. DetWoORAM logically partitions the memory into a main area and a holding area. The actual pages are stored in main area. We propose two enhancements over DetWoORAM that improves the application execution slowdown. The first enhancement, which we call the Eager DetWoORAM, involves page preloading that exploits the deterministic access pattern of DetWoORAM, and tries to hide the ORAM latency. The second enhancement, which we call the Parallel DetWoORAM, involves spawning multiple threads and each thread performs a part of the DetWoORAM memory access algorithm. Compared to DetWoORAM that shows slowdown of [1.4x, 2x, and 3.24x], Eager DetWoORAM and Parallel DetWoORAM provide slowdown of [1.2x, 1.8x, and 3.2x] and [1.1x, 1.1x, and 1.4x], for k= 3, 7, and 15, respectively.
Faster Sparse Matrix Inversion and Rank Computation in Finite Fields

We improve the current best running time value to invert sparse matrices over ﬁnite ﬁelds, lowering it to an expected O (cid:0) n 2 . 2131 (cid:1) time for the current values of fast rectangular matrix multiplication. We achieve the same running time for the computation of the rank and nullspace of a sparse matrix over a ﬁnite ﬁeld. This improvement relies on two key techniques. First, we adopt the decomposition of an arbitrary matrix into block Krylov and Hankel matrices from Eberly et al. (ISSAC 2007). Second, we show how to recover the explicit inverse of a block Hankel matrix using low displacement rank techniques for structured matrices and fast rectangular matrix multiplication algorithms. We generalize our inversion method to block structured matrices with other displacement operators and strengthen the best known upper bounds for explicit inversion of block Toeplitz-like and block Hankel-like matrices, as well as for explicit inversion of block Vandermonde-like matrices with structured blocks. As a further application, we improve the complexity of several algorithms in topological data analysis and in ﬁnite group theory.
A System-Level Voltage/Frequency Scaling Characterization Framework for Multicore CPUs

Supply voltage scaling is one of the most effective techniques to reduce the power consumption of microprocessors. However, technology limitations such as aging and process variability enforce microprocessor designers to apply pessimistic voltage guardbands to guarantee correct operation in the field for any foreseeable workload. This worst-case design practice makes energy efficiency hard to scale with technology evolution. Improving energy-efficiency requires the identification of the chip design margins through time-consuming and comprehensive characterization of its operational limits. Such a characterization of state-of-the-art multi-core CPUs fabricated in aggressive technologies is a multi-parameter process, which requires statistically significant information. In this paper, we present an automated framework to support system-level voltage and frequency scaling characterization of Applied Micro’s state-of-the-art ARMv8-based multicore CPUs used in the X-Gene 2 micro-server family. The fully automated framework can provide fine-grained information of the system’s state by monitoring any abnormal behavior that may occur during reduced supply voltage conditions. We also propose a new metric to quantify the behavior of a microprocessor when it operates beyond nominal conditions. Our experimental results demonstrate potential uses of the characterization framework to identify the limits of operation for improved energy efficiency.
Weakly Supervised Pre-Training for Multi-Hop Retriever

In multi-hop QA, answering complex questions entails iterative document retrieval for finding the missing entity of the question. The main steps of this process are sub-question detection, document retrieval for the sub-question, and generation of a new query for the final document retrieval. However, building a dataset that contains complex questions with sub-questions and their corresponding documents requires costly human annotation. To address the issue, we propose a new method for weakly supervised multi-hop retriever pre-training without human efforts. Our method includes 1) a pre-training task for generating vector representations of complex questions, 2) a scalable data generation method that produces the nested structure of question and sub-question as weak supervision for pre-training, and 3) a pre-training model structure based on dense encoders. We conduct experiments to compare the performance of our pre-trained retriever with several state-of-the-art models on end-to-end multi-hop QA as well as document retrieval. The experimental results show that our pre-trained retriever is effective and also robust on limited data and computational resources.
Study of rotational splittings in δ Scuti stars using pattern finding techniques

Detecting and understanding rotation in stellar interiors is nowadays one of the unsolved problems in stellar physics. Asteroseismology has been able to provide insights on rotation for the Sun, solar-like stars, and compact objects like white dwarfs. However, this is still very difficult for intermediate-mass stars. These stars are moderate-to-rapid rotators. Rotation splits and shifts the oscillation modes, which makes the oscillation spectrum more complex and harder to interpret. Here we study the oscillation patterns of a sample of benchmark δ Sct stars belonging to eclipsing binary systems with the objective of finding the frequency spacing related to the rotational splitting (δr). For this task, we combine three techniques: the Fourier transform, the autocorrelation function, and the histogram of frequency differences. The last two showed a similar behaviour. For most of the stars, it was necessary to determine the large separation (Δν) prior to spot δr. This is the first time we may clearly state that one of the periodicities present in the p modes oscillation spectra of δ Sct stars corresponds to the rotational splitting. This is true independent of the stellar rotation rate. These promising results pave the way to finding a robust methodology to determine rotational splittings from the oscillation spectra of δ Sct stars and, thus, understanding the rotational profile of intermediate-mass pulsating stars.