Miracle-dz/UniFAR-FTUs huggingface dataset:
INS Alignment Using Onboard Computer Software for Missile Trajectory

In this paper, the onboard computer software program was developed to predict the full trajectory of the missile in order to improve the accuracy at impact. For system in which time is not critical, the alignment process can be performed prior to launch by utilizing navigation data from the launch platform and calibrating the missile’s INS to this reference. However, for systems that require rapid reaction time, significant pre-launch delays for alignment are not tolerable. In addition, due to low quality of the INS and its life cycle is short; hence every aborted mission will bring the INS closer to its mean time between failures (MTBF). These problems can be minimized by in-flight alignment (IFA). While IFA may seem to be less accurate and more complicated than alignment in the rest, it turns out that the ability of the carrier to maneuver during the IFA phase is a blessing in disguise since it enables the excitation of latent modes and thus, enhances their observability of the whole INS. The effects that maneuvers have on the estimability of the INS states during IFA were investigated in the past. But until now, there are many questions such as: what is the degree of observability? What limits the estimability of the system? What are the minimal additional measurements needed to turn the system into a completely observable one? And what are the useful numbers of maneuvers in IFA? , were not completely addressed. These questions are answered through this paper. We introduce the error model, which appropriately describes the INS behavior during IFA. We then substantiate its adequacy for consideration as a piece-wise constant system (PWCS) and then the simpler stripped observability matrix (SOM) can be used in the system observability analysis.
Developing revised Fama-French Five-Factor models by including dividend rate, cash holdings, and Free cash flow to equity: evidence of Tehran stock exchange

Prediction of stock returns has always been one of the most important issues in finance. Investors have attracted to use of Fama-French Five-Factor Model (FFFFM) as one of the powerful methods for pricing financial assets and predicting the stock returns. This research investigates the predictability of stock returns by including some important firms features namely cash holdings, dividend rate, and free cash flow to equity to FFFFM. Statistical samples consist of 75 companies listed on the Tehran Stock Exchange (TSE) during 2003-2017. The results of panel data test indicate positive significant effects of all variables in FFFFM (i.e. book to market value ratio, company size, growth opportunity, profitability, and investment) as well as newly added firms feature variables (cash holding, dividend rate, and free cash flow to equity). However, the investment has a negative impact on the returns due to the initial estimate of primary FFFFM. In addition, the results indicate that the inclusion of firms feature variables significantly improve the predictive power of stock returns. Finally, by comparing the predictive power of the models, the best prediction model is determined.
Introduction to the Handbook of Research on the Psychological Contract at Work

The psychological contract is “an individual’s beliefs regarding the terms and conditions of a reciprocal exchange agreement between the focal person and another party” (Rousseau, 1989, p. 123). The psychological contract represents the employee’s mental model or cognitive schema about the exchange relationship with the employer. This schema com-prises the employee’s perceived mutual obligations to contribute certain resources (e.g., time, loyalty, work effort) to the organization, as well as the organization’s obligation to contribute certain resources (e.g., com-petitive pay, training and development, flexible working hours) in return. The psychological contract influences the employee’s interpretation of employer actions (or non-actions) and guides employee emotions, attitudes, and behavior toward the organization. Decades of research have shown that perceived psychological contract fulfillment is associated with positive employee attitudes and behaviors, whereas perceived psychological contract breach is associated with negative such reactions (for a meta-analysis see Bal, De Lange, Jansen, & van der Velde, 2008; Zhao, Wayne, Glibkowski, & Bravo, 2007). Despite the common usage of the concept, there is considerable evidence that the concept does not have the analytical rigor of more enduring psychological constructs and as such it is not only being misused, but also being diminished as an explanatory framework.
Genetic and morphometric analyzes of Paralichthys species confirm the presence of P. brasiliensis in the Uruguayan waters

ABSTRACT Paralichthys species have high commercial value and constitute a resource for demersal fisheries in the Southwestern Atlantic Ocean. Although six species have been described based on morphological characters for the Uruguayan and Argentinean waters, only the presence of three species is accepted, being their distribution still uncertain. Genetic tools are useful for species identification as a complement of morphological characters. This paper determines the genetic and morphometric variation between three species of Paralichthys that inhabiting Uruguayan waters. The interorbital width (IN) and the length from the mouth to the dorsal fin base (SD) of P. patagonicus differed significantly from the other two species (P. orbignyanus and P. brasiliensis). From a morphological perspective, individuals identified as P. orbignyanus formed two different groups. Clade Po_A included those belonging to oceanic coastal waters of Uruguay and deeper waters of the Rio de la Plata together with individuals of P. brasiliensis from ItajaÃ, Santa Catarina (Brazil). Individuals collected in the Rio de la Plata coastal and beach zone formed the clade Po_B group. Genetic analysis confirmed for the first time the presence of P. brasiliensis in Uruguayan and Rio de la Plata shelf waters and extends its known distribution area further south. Discriminant scores for P. orbygnianus separate individuals in two groups corresponding to the presence of two species. Molecular and morphological analysis showed individuals in the clade Po_A includes those collected in Uruguayan waters together with those collected in northern Brazilian waters belonging to the species P. brasiliensis.
Development of Basketball Passing Learning Model with A Play Approach to Students Junior High School

This research and development aims to produce a product of passing basket ball learning models with a play approach to junior high school students and test the effectiveness of these products. The design of this study refers to the research and development model (Research and Development) of Borg and Gall. Broadly speaking, the development steps for the purposes of this research are carried out in 4 stages, namely: preliminary research, model development planning, evaluation evaluation of model revisions, and model implementation. The effectiveness test of the model uses a basketball passing instrument using the t-test one group pretest-posttest design . The results of the effectiveness test were 6.83 when the pre test increased to 10.25 after the post test, an increase of 28.06%. From the results of data analysis it is evident that there was an increase in the results of the pre test and post test for both male and female students. Based on the results of the study, it was proven empirically that the product results in the form of a passing basketball learning model with an approach to play in junior high school students had very good effectiveness and could be implemented.
Fixing What’s Most Broken in the US Immigration System: A Profile of the Family Members of US Citizens and Lawful Permanent Residents Mired in Multiyear Backlogs

Executive Summary The US Department of State (DOS) reports that as of November 2018, nearly 3.7 million persons had been found by US Citizenship and Immigration Services (USCIS) to have a close family relationship to a US citizen or lawful permanent resident (LPR) that qualified them for a visa, but were on “the waiting list in the various numerically-limited immigrant categories” (DOS 2018). These backlogs in family-based “preference” (numerically capped) categories represent one of the most egregious examples of the dysfunction of the US immigration system. They consign family members of US citizens and LPRs that potentially qualify for a visa and that avail themselves of US legal procedures to years of insecurity, frustration, and (often) separation from their families. Often criticized in the public sphere for jumping the visa queue, it would be more accurate to say that this population, in large part, comprises the queue. While they wait for their visa priority date to become current, those without immigration status are subject to removal. In addition, most cannot adjust to LPR status in the United States, but must leave the country for consular processing and, when they do, face three- or 10-year bars on readmission, depending on the duration of their unlawful presence in the United States. This population will also be negatively affected by the Department of Homeland Security’s (DHS) proposed rule to expand the public charge ground of inadmissibility (Kerwin, Warren, and Nicholson 2018). In addition, persons languishing in backlogs enjoy few prospects in the short term for executive or legislative relief, given political gridlock over immigration reform and the Trump administration’s support for reduced family-based immigration.
A Black-Box Approach for Estimating Utilization of Polled IO Network Functions

Cloud management tasks such as performance diagnosis, workload placement, and power management depend critically on estimating the utilization of an application. But, it is challenging to measure actual utilization for polled IO network functions (NFs) without code instrumentation. We ask if CPU events (e.g., data cache misses) measured using hardware performance counters are good at estimating utilization for polled-IO NFs. We find a strong correlation between several CPU events and NF utilization for three representative types of network functions. Inspired by this finding, we explore the possibility of computing a universal estimation function that maps selected CPU events to NF utilization estimates for a wide-range of NFs, traffic profiles and traffic loads. Our NF-specific estimators and universal estimators achieve absolute estimation errors below 6% and 10% respectively.
Outcome estimation based on multimodal computed tomography examination in acute ischaemic stroke patients treated with mechanical thrombectomy

Introduction Reperfusion therapy for acute ischaemic stroke used within a time window of 6 h following symptom onset, although currently the treatment of choice, is characterised by certain limitations and carries certain risks. Aim To assess the potential for predicting the risks and limitations of reperfusion therapy by means of advanced neuroimaging. Material and methods For this purpose, the baseline CT scans of patients with ischaemic stroke treated by means of mechanical thrombectomy were assessed retrospectively using the Combined Multimodal Computed Tomography Score (CMCTS), modified to account for the perfusion examination of a limited area. These data were then combined with radiological and clinical outcomes, in particular haemorrhagic stroke transformation and scoring on a modified Rankin scale (mRS). Results Based on material from 85 patients, the scoring system we employed enabled us to distinguish a group that did not benefit from treatment with specificity and a positive predictive value of 100%, and a negative predictive value of 64%. Neither the relationship between the score and early haemorrhagic complications, nor the effectiveness or severity of the course of the thrombectomy procedure itself was confirmed. Conclusions There is no justification for the use of reperfusion procedures in acute ischaemic stroke in the anterior circulation in patients with initially unfavourable multimodal computed tomography scores.
Assessment of Scale Invariance Changes in Heart Rate Signal During Postural Shift

In this study, heart rate time series have been investigated to assess the presence of scale invariance property of a signal. The electrocardiogram signal is recording from Biopac MP100 system during postural shift from supine to standing. Heart rate time series is extracted from electrocardiogram signal and is analyzed using detrended fluctuation analysis. Since this analysis is based on random walk theory, noise level due to imperfect measurement in recording is reduced and it can systematically eliminate trends of different orders. The essence of this method is to understand the presence of scale invariance in heart rate and to classify the scaling factor changes during postural shift from supine to standing. The obtained scaling factor is invariant with respect to scale sizes, which confirm that heart rate signal is scale invariant. In addition, scaling factor is significantly less for supine position as compared with the standing indicates it is directly proportional to heart rate. Therefore, this method helps in calculating the risk to evaluate the patient status during postural changes to obtain information about heart instability.
Design and Research of a Broadband High-Gain Low-Profile Antenna

A broadband high-gain low-profile array antenna with a brick structure is presented in this paper. The array antenna is arranged in a $2 \times 4$ configuration, and a printed dipole antenna is taken as the element. Two elements along the E-plane are printed on a substrate as a subarray, and four subarrays along the H-plane are arranged orthogonally to the four-way power divider, meaning that the array is a brick structure. The proposed antenna can provide a relative bandwidth of 40% in the frequency range 1.2–1.8 GHz with return loss (RL) greater than 13 dB, a gain greater than 14 dBi, and a height less than 4/10 of the wavelength of the center frequency. The radiation efficiency of the proposed antenna is between 40% and 80% across the operating bandwidth as well as the horn antenna, and the height is only 1/8 of the horn antenna with the same aperture. Finally, a high-gain low-profile antenna with 17 and 20 dBi is provided, which has the same radiation efficiency as the horn, and this design is verified to be equally applicable to antennas with a higher gain.
The Determinants of Inflation in West Africa

The objective of this study is to identify the determinants of inflation in West Africa, mainly in the WAEMU zone, in order to contribute to improving the conduct of monetary policy. The equation of the exchange of the Quantitative Theory of the Currency and the generalized method of moments (MMG) in dynamic panel is used. Annual data concerning six countries in West Africa and range from 1991 to 2015. The results of the estimation show that in addition to the economic growth rate and the money supply, the devaluation has a significant effect on inflation. As we can see, inflation is not systematically a monetary phenomenon in West Africa. The authorities must therefore seek to determine the optimal threshold for the rate of increase of the money supply.
The complete genome sequence and annotation of a psychrophilic Cryobacterium species GCJ02 isolated from cryomorphic soil of a virgin forest

A novel psychrotroph Cryobacterium sp. GCJ02 was isolated and characterized, which showed gorwth well at 4 ºC. The assembled whole genome of strain GCJ02 is 4.39 Mb, including 4,139 protein coding genes with G+C content of 68.41mol%. In this study, we report the complete genome sequence of a novel strain of the genus Cryobacterium, affording feasibility to elucidate the molecular mechanism of cold adaptation, and facilitate genetic manipulation of this bacterium.
Pre-history of probability

It has been common to begin histories of probability with the calculations of Fermat and Pascal on games of chance in 1654. Those calculations were the first substantial mathematical results on stochastic phenomena, which, according to a frequentist philosophy of probability, are the true subject-matter of the field. But there is great philosophical interest in studying earlier ideas. That is because we see a struggle to understand a range of basic concepts about probability and uncertain evidence, before the straightjacket of a single formalization was imposed. There is still much to learn from seeing how the problems now studied with the aid of probability theory were dealt with in “bare hands” fashion before that formalization was available.
Down in the dumps: Analysis of glass production debris from Petrie's excavations at Amarna

Sir Flinders Petrie’s excavations at Tell el-Amarna in Egypt (1891-1892) uncovered a large number of glass finds and vitreous debris from areas identified as palace trash heaps and industrial buildings, suggesting that glass was produced at the site as early as the fourteenth century BC. His findings, combined with those from recent archaeological investigations and chemical analyses, highlight the important role Amarna played in early glass technology and its significance as a location for glass production, both locally and abroad, during thelatter part of the Late Bronze Age (sixteenth-eleventh century BC).
Association between Personality and Financial Well-being: Strategies for More Effective Financial Education, Counseling and Advising

Introduction Philosophically and psychologically, there is an argument that personality is either an inherited trait or a trait developed during a person’s lifetime. In other words, there is a controversial debate whether personality is changeable or not. However, regardless the debate about changeability of personality, there are empirical research findings to show the significant relevance among personality, well-being, and financial management (Brüggen, Hogreve, Holmlund, Kabadayi, & Löfgren, 2017; Creed & Evans, 2002; Donnelly, Iyer, & Howell, 2012; Johnston, Kassenboehmer, & Sheilds, 2016; Luhmann, Hofman, Eid, & Lucas, 2012; Xu, Beller, Roberts, & Brown, 2015). Research implies that personality relates to financial well-being. However, few attempts have been made to find the direct association between personality traits and financial well-being. The main objective of the study is to determine whether personality is significantly associated with financial well-being. A significant association between personality and financial well-being could aid financial educators, counselors, and advisors in developing strategies to meet the financial management needs of consumers. An outcome of financial education/counseling/advising is to improve financial wellbeing, implementing strategies that specifically target personality characteristics could lead to successful results. For instance, a specific type of personality identified by the client could aid the educator/counselor/advisor in determining the appropriate financial management strategy a client would need to implement to improve their financial well-being. This study utilizes the Big-Five personality traits (John & Srivastava, 1999) for the survey research. The Big Five personality traits are: (a) extraversion vs. introversion, (b) agreeable vs. antagonism, (c) conscientiousness vs. lack of direction, (d) neuroticism vs. emotional stability, and (e) openness vs. closedness to experience. The main hypotheses of the study are: H1a: Extroversion personality is significantly associated with financial well-being. H2a: Agreeable personality is significantly associated with financial well-being. H3a: Conscientious personality is significantly associated with financial well-being. H4a: Neurotic personality is significantly associated with financial well-being. H5a: Open personality is significantly associated with financial well-being.
Implementation and Experimental Verification of Flow Rate Control Based on Differential Flatness in a Tilting-Ladle-Type Automatic Pouring Machine

In this paper, we study an advanced pouring control system using a tilting-ladle-type automatic pouring machine. In such a machine, it is difficult to precisely pour the molten metal into the pouring basin of the mold, as the outflow from the ladle can be indirectly controlled by controlling its tilt. Therefore, model-based pouring control systems have been developed as a part of conventional studies to solve this problem. In the results of a recent study, the efficacy of a pouring flow rate control system based on differential flatness has been verified, by performing a simulation. In this study, we apply the flow rate control system based on differential flatness to a tilting-ladle-type automatic pouring machine, using experiments to verify the efficacy of the flow rate control system in suppressing any disturbances. In these experiments, the tracking performance using the developed flow rate control system was better than the performance obtained using a conventional feed-forward-type flow rate control system.
CkLR Algorithm for Improvement of Data Prediction and Accuracy Based on Clustering Data

In this paper, we proposed the CkLR algorithm to build a model to analyze the response variables of clustered outcomes with a K-means algorithm to categorize and analyze unstructured data such as SNS and assess the prediction rate of clustering and its accuracy rate after the entry of new data. CkLR performs a neural network algorithm based on the clustering outcomes of the data classified in the previous stage. The CkLR model applies a neural network to reflect the entire form of data learning methods rather than stepwise data learning based on clustering data, and conducts research to select a neural network model and analyze variables through learning by clustering. The datasets of the input clustering outcomes are adjusted at certain percentages (learning, testing, and evaluation) to check the prediction rate of input outcomes. The study also proposed a CkLR algorithm based on an LSTM recurrent neural network to compensate for the problem of determining the size of input and output value data for each repetition in a single training session. The training structure of the proposed prediction model, based on a neural network, would calculate the loss values of training, minimize them, and select an optimal model reflecting weights in case of clustering sequential data. The performance evaluation results demonstrate that it recorded prediction and accuracy rates that were 3.65% higher than the old single neural network structure through individual neural networks.