Miracle-dz/UniFAR-FTUs huggingface dataset:
A frequentist analysis of the n=3 type-I seesaw model

The extension of the Standard Model by right-handed neutrinos can not only explain the active neutrino masses via the seesaw mechanism, but is also able to answer a number of open questions in cosmology. In particular, masses below the TeV scale are of interest as they can lead to a plethora of signatures in experimental searches. In the thesis, the first full frequentist analysis of this extension of the Standard Model by three right-handed neutrinos, with masses between 60 MeV and 500 GeV, using the Global and Modular BSM Inference Tool (GAMBIT) is presented. The analysis is based on the Casas-Ibarra parameterization and includes a large range of experimental constraints: active neutrino mixing, indirect constraints from, e.g., electroweak precision observables and lepton universality, and numerous direct searches for right-handed neutrinos. To study their overall effect, combined profile likelihood results for the most relevant (phenomenologically) parameter projections are derived. Furthermore, the role of (marginally) statistically preferred regions in the parameter space is discussed. Finally, the flavour mixing pattern of the three right-handed neutrinos for different values of the lightest neutrino mass are explored. The results comprise the most comprehensive assessment of the model with three right-handed neutrinos below the TeV scale so far, and provide a robust ground for exploring the impact of future constraints or detections.
A High Performance File System for Non-Volatile Main Memory

: Emerging Non-Volatile Main Memories (NVMMs) are expected to be next-generation storage. These memories promise to enable persistent memory, which can store data persistently at the main memory level with low latency. Therefore, the traditional primary storage hierarchy is extended to the non-volatile part by them. Integrating NVMM into computer systems includes some interesting challenges though they are expected to realize a fast and reliable computer system when using them. We explore NVMMs feature and how to handle them e ﬃ ciently as main storage through developing a new ﬁle system in the Linux kernel which exploits memory hierarchy including NVMMs
Effects of virtual reality combined with balance training on upper limb function, balance, and activities of daily living in persons with acute stroke: a preliminary study

Objective: The aim of this preliminary study was to investigate the effects of virtual reality combined with balance training on upper limb function, balance, and activities of daily living (ADL) in persons with acute stroke. Design: Randomized controlled trial. Methods: Fourteen acute stroke survivors were recruited and randomly assigned into two groups: the experimental group (n=7) and the control group (n=7). Both groups performed the conventional rehabilitation therapy for 30 minutes a day, 5 times a week, for 4 weeks. Additionally, the experimental group conducted the virtual reality training for 30 minutes on an unstable surface during each session, whereas the control group performed balance training for 30 minutes on a stable surface. All measurements were performed before and one day after intervention. Upper limb function, balance, and ADL were assessed using the Manual Function Test (MFT), the Berg Balance Scale (BBS), and the Korean version of the Modified Barthel Index (K-MBI), respectively. Results: Both groups showed significant improvements in MFT, BBS, K-MBI after intervention ( p <0.05). There were no significant differences between the experimental and control groups with respect to MFT, BBS, and K-MBI after intervention. The experimental group showed a greater decrease in fall risk (BBS<45) after intervention than the control group ( p <0.05). Conclusions: These findings suggest that virtual reality combined with balance training has a better effect on balance improvement than virtual reality training alone in persons with acute stroke.
Wise academic development: learning from the ‘failure’ experiences of retired academic developers

ABSTRACT Informed by Constructive Developmental Theory and the Threshold Concepts Framework, we interviewed retired academic developers from four continents and asked them to describe their processes of learning from perceived failures and how they see the role of academic developers in supporting academics through failures. Findings regarding participants’ definitions of failure, ways of making sense of and learning from failure, and recommendations for supporting academic colleagues’ learning from failure are shared through tables, quotations, and poetry. Findings show that ‘wise academic development’ embraces curiosity about failure, integrates the (sometimes) transformative nature of failure, shares the load of sense-making, and cultivates connectedness.
The cosine geometric distribution with count data modeling

In this paper, a new two-parameter discrete distribution is introduced. It belongs to the family of the weighted geometric distribution (GD), with the feature of using a particular trigonometric weight. This configuration adds an oscillating property to the former GD which can be helpful in analyzing the data with over-dispersion, as developed in this study. First, we present the basic statistical properties of the new distribution, including the cumulative distribution function, hazard rate function and moment generating function. Estimation of the related model parameters is investigated using the maximum likelihood method. A simulation study is performed to illustrate the convergence of the estimators. Applications to two practical datasets are given to show that the new model performs at least as well as some competitors.
Green Skills Understanding of Agricultural Vocational School Teachers around West Java Indonesia

This study investigated understanding of agricultural vocational school teachers about green skills and its entity in the curriculum. Data were gathered through survey of teachers from fifteen agricultural vocational high school of agricultural food processing technology study program in West Java Province, Indonesia regarding their understanding about green skills. The results showed that the teachers had less knowledge of green skills, limited to environmental issues. However, they agreed that students needed to be equipped with green skills. The entity of green skills has not been stated explicitly in the curriculum of agricultural vocational school. However, the teachers argued that green skills could be embedded in the subjects of the existing curriculum. The findings of this preliminary study indicated the need to increase teacher understanding of green skills and curriculum development in agricultural vocational schools to meet industrial needs in order to support sustainable development in accordance with the UNESCO strategy for vocational education.
Shared Control Between Human Driver and Automation in Cooperative Driving Based on Game Theoretic Model Predictive Control

Shared control is a control framework in which control action is shared between a human driver and an automation. In this work, the shared control is studied based on game theoretical approach of distributed model predictive control (DMPC). The solution of cooperative game is derived under DMPC framework, and then realistic driving situation is studied in cooperative game framework. Shared control strategy for fully mixed driving authority is proposed considering collision probability based on TTC (time to collision) and tracking error. Simulations were conducted using Matlab/Simulik in cooperative driving. The simulation scenarios consist of safety critical situation and non-safety critical situation. In safety critical situation, an automation takes more control authority to avoid a collision, and in non-safety critical situation a human driver takes more control authority. The simulation results show that the control authority is shared continuously by the proposed shared control strategy.
KONTRIBUSI SIKAP DISIPLIN DAN MOTIF BERKOMPETISI TERHADAP KOMPETENSI PENGETAHUAN IPS SISWA KELAS IV

Penelitian ini bertujuan untuk mengetahui pengaruh yang signifikan sikapdisiplin dan motif berkompetisi terhadap kompetensi pengetahuan IPS siswakelas IV SDN Gugus Mohhamad Hatta Kecamatan Denpasar Selatan TahunAjaran 2018/2019. Penelitian ini merupakan penelitian ex post facto.Populasi penelitian ini seluruh siswa kelas IV SDN Gugus Mohhamad HattaKecamatan Denpasar Selatan Tahun Ajaran 2018/2019 berjumlah 243 siswa.Sampel ditentukan dari populasi menggunakan teknik proportional randomsampling. Jumlah sampel dari populasi adalah 142 siswa. Metode teknikpengumpulan data menggunakan metode non tes berupa pencatatandokumen dan angket. Data sikap disiplin dan motif berkompetisi diperolehmelalui angket, data kompetensi pengetahuan IPS melalui pencatatandokumen. Setelah data diperoleh, dilakukan uji prasyarat analisis dengan ujinormalitas Kolmogorov-Smirnov, uji linearitas, uji multikolinearitas dan ujiheteroskedastisitas. Data penelitian yang telah memenuhi uji prasyaratanalisis diuji menggunakan analisis statistik inferensial dengan teknikanalisis regresi ganda. Hasil penelitian menunjukkan pengaruh yangsignifikan antara sikap disiplin dan motif berkompetisi terhadapkompetensi pengetahuan IPS berdasarkan nilai Fhitung = 3,13 > Ftabel = 3,07dengan kontribusi sebesar 4,3%. Sikap disiplin dan motif berkompetisimemberikan kontribusi sebesar 4,3% terhadap kompetensi IPS pada siswakelas IV SDN Gugus Mohhamad Hatta Kecamatan Denpasar Selatan.Sehingga 95,7% lainnya dipengaruhi oleh faktor belajar lain baik faktor daridalam maupun faktor dari luar diri siswa. Adapun saran ditujukan kepadaguru untuk lebih mengoptimalkan sikap disiplin dan motif berkompetisidalam pembelajaran guna dapat mencapai kompetensi pengetahuan IPS.
Blockchain Security in MANETs

—The security aspect of the IoT occupies a place of great importance especially after the evolution that has known this ﬁeld lastly because it must take into account the transformations and the new applications . Blockchain is a new technology dedicated to the data sharing. However, this does not work the same way in the different systems with different operating principles. This article will discuss network security using the Blockchain to facilitate the sending of messages and information, enabling the use of new processes and enabling autonomous coordination of devices. To do this, we will discuss proposed solutions to ensure a high level of security in these networks in the work of other researchers. Finally, our article will propose a method of security more adapted to our needs as a team working in the ad hoc networks, this method is based on the principle of the Blockchain and that we named ”MPR Blockchain”.
Non-invasive central venous pressure estimation by ultrasound-guided internal jugular vein cross-sectional area measurement

Purpose. Central venous pressure (CVP) is widely used in clinical practice as a tool in assessment of fluid status and fluid responsiveness. It is however an invasive monitoring tool and fraught with many untoward complications. This research aims to ascertain if ultrasound-guided measurements of the cross-sectional area (CSA) of the internal jugular vein (IJV) has any correlation with conventional CVP values. Methods. A prospective observational study was conducted for a period of two months. Patients presenting to the operating room or admitted to the Intensive Care Unit who had placement of a central venous catheter were sequentially selected and informed consent obtained. All patients had their right IJV dimensions measured by ultrasound using a high frequency 12 MHz vascular surface probe. Measurements obtained included the CSA and circumference of the IJV before insertion of the central line. Central line was placed, CVP was then recorded and the CVP values and the IJV dimensions were correlated. Results. A total of 43 patients were enrolled, but valid data were obtained only from 40. There was a strong correlation between the CSA of IJV with CVP readings (Pearson correlation coefficient, r = 0.559, p < 0.001). Also the correlation between the circumference and recorded CVP was found to be statistically significant (r = 0.481, p < 0.001). Regression formulae were constructed to calculate CVP from IJV circumference as well as CSA. Conclusions. There is a strong correlation between sonographically measured IJV CSA and catheter-measured CVP. In patients having contraindications for a central catheter, non-invasive sonographic measurement of CVP may be a reliable option.
Autonomous State Estimation and Mapping in Unknown Environments With Onboard Stereo Camera for Micro Aerial Vehicles

Industrial micro aerial vehicles (MAVs) with robotic manipulators have numerous applications in search and rescue tasks that reduce risks to human beings. However, such tasks distinctly require MAVs to have the capability of real-time autonomous navigation only with onboard sensors, especially in GPS-denied applications. This article introduces a new approach to onboard vision-based autonomous state estimation and mapping for MAVs’ navigation in unknown environments. The algorithms run on board and do not need an external positioning system to assist autonomous navigation. The state estimator is developed to provide MAV's current pose on the basis of the extended Kalman filter by using image patch features. Inverse depth convergence monitoring and local bundle adjustment are utilized to improve the accuracy. The mapping algorithm for navigation is developed according to a real-time stereo matching method for three-dimensional perception. Finally, we have performed several experiments to demonstrate the effectiveness of the proposed approach.
Marijuana use, fetal growth, and uterine artery Dopplers

Abstract Objective Marijuana (MJ) use is associated with adverse effects on fetal growth. We aimed to investigate the timing of suboptimal fetal growth onset in MJ-exposed pregnancies. In addition, we aimed to explore the relationship between MJ-exposure and both abnormal uterine artery (UtA) Doppler parameters and small for gestational age (SGA). Study design This was a secondary analysis of a prospective multicenter cohort that enrolled nulliparous individuals delivering non-anomalous fetuses beyond 20 weeks’ gestation. Marijuana exposure was ascertained by self-report or clinical urine toxicology testing. Ultrasound estimated fetal weights (EFWs) were assessed in participants at both 16w0d–21w6d and 22w0d–29w6d. EFWs and birth weight (BW) were converted to weight percentiles (wPCT). EFW and BW wPCTs were calculated using population-based standards. Additionally, a customized standard designed to be applicable to both EFWs and BWs within the same model was also used to allow for EFW to BW percentile trajectories. The primary outcome, longitudinal wPCT, was compared between individuals with and without MJ use in a linear mixed-effects regression model adjusting for tobacco. For modeling, wPCT was smoothed across gestational age; MJ was estimated as an intercept and linear difference in the slope of gestational age. UtA Doppler notching, resistance index (RI), and pulsatility index (PI) at 16w0d–21w6d were compared using t-test and χ 2. SGA at delivery was also compared. Results Nine thousand one hundred and sixty-three individuals met inclusion criteria; 136 (1.5%) used MJ during pregnancy. Individuals who used MJ were more likely to be younger, identify as non-Hispanic Black, and have had less education. Fetuses exposed to MJ had lower wPCT beginning at 28 weeks using population-based and customized standards, when compared to those without exposure. UtA notching, PI, and RI were similar between groups. SGA was more frequent in neonates exposed to MJ using both population-based (22 vs. 9%, p<.001) and customized (25 vs. 14%, p<.001) curves. Conclusions MJ-exposed fetuses were estimated to be smaller than unexposed fetuses starting at 28 weeks’ gestation across both growth standards without a difference in UtA Doppler parameters.
Model Predictive Current Control for an Open-Winding PMSM System With a Common DC Bus in 3-D Space

Improved model predictive current control (MPCC) strategies in 3-D space are proposed in this article for an open-winding permanent-magnet synchronous motor (OW-PMSM) system with a common dc bus. In order to simply determine the optimal voltage vector (VV), a cost function related to VVs is established to replace that related to stator currents in conventional MPCC and the weighting factors are obtained by theoretical derivation. In order to reduce the calculation time of the optimal VV, a 3-D space system is established and the candidate VVs and the reference VV can be placed in the 3-D space. Then by means of the space geometric theory, the optimal VV can be selected faster and only four calculations are required in each sampling period. For better tracking of the reference VV, a VV-tracking (VVT) MPCC strategy is proposed and three VVs are selected according to the volt–second balance principle. Experimental results verify the effectiveness of the proposed strategies.
Longitudinal Study of the Variation in Patient Turnover and Patient-to-Nurse Ratio: Descriptive Analysis of a Swiss University Hospital

Background Variations in patient demand increase the challenge of balancing high-quality nursing skill mixes against budgetary constraints. Developing staffing guidelines that allow high-quality care at minimal cost requires first exploring the dynamic changes in nursing workload over the course of a day. Objective Accordingly, this longitudinal study analyzed nursing care supply and demand in 30-minute increments over a period of 3 years. We assessed 5 care factors: patient count (care demand), nurse count (care supply), the patient-to-nurse ratio for each nurse group, extreme supply-demand mismatches, and patient turnover (ie, number of admissions, discharges, and transfers). Methods Our retrospective analysis of data from the Inselspital University Hospital Bern, Switzerland included all inpatients and nurses working in their units from January 1, 2015 to December 31, 2017. Two data sources were used. The nurse staffing system (tacs) provided information about nurses and all the care they provided to patients, their working time, and admission, discharge, and transfer dates and times. The medical discharge data included patient demographics, further admission and discharge details, and diagnoses. Based on several identifiers, these two data sources were linked. Results Our final dataset included more than 58 million data points for 128,484 patients and 4633 nurses across 70 units. Compared with patient turnover, fluctuations in the number of nurses were less pronounced. The differences mainly coincided with shifts (night, morning, evening). While the percentage of shifts with extreme staffing fluctuations ranged from fewer than 3% (mornings) to 30% (evenings and nights), the percentage within “normal” ranges ranged from fewer than 50% to more than 80%. Patient turnover occurred throughout the measurement period but was lowest at night. Conclusions Based on measurements of patient-to-nurse ratio and patient turnover at 30-minute intervals, our findings indicate that the patient count, which varies considerably throughout the day, is the key driver of changes in the patient-to-nurse ratio. This demand-side variability challenges the supply-side mandate to provide safe and reliable care. Detecting and describing patterns in variability such as these are key to appropriate staffing planning. This descriptive analysis was a first step towards identifying time-related variables to be considered for a predictive nurse staffing model.
Energy Sector CO2 Emission In Palm Oil Mill

The palm oil industry contributes to produce Green House Gases (GHG) from the land conversion sector, energy use, industrial processes and residual waste from palm oil production. Energy is one of the important sectors in the inventory of GHG emissions. In energy consumption, GHGs are generated from the use of diesel fuel, burning shells and fiber. In addition to the use of diesel as its main fuel, shells and fiber are utilized for fuel. In this study, the calculation of the amount of emissions produced from palm oil mills in the energy sector was calculated according to the 2006 IPCC Guidelines Volume 2 Chapter 2 concerning the Stationary Combustion. The calculation results obtained by the average emissions produced in observed palm oil mill for the energy sector is 1,570,883 kg CO2/year or 1.5 Gg CO2/year.
Quality of Life Outcomes of Iranian Traditional Medicine Health Measures Instruction (Hefzalsehe): A Clinical Trial

Background: The sedentary lifestyle violates health status and has negative impacts on the quality of life with subsequently numerous diseases. Objectives: The current study aimed at evaluating the quality of life outcomes of Iranian traditional medicine (ITM) health protection measures instruction (traditionally named Hefzalsehe meaning that the essential lifestyle recommendations to maintain health and well-being based on ITM). Methods: The current randomized, controlled trial aimed at examining the quality of life outcomes of ITM health protection measures instruction (Hefzalsehe) in individuals in Tehran, Iran in 2017. At the same interval, the experimental group was trained vir-tually and traditionally for the ITM health protection measures; whereas the control group was not. Subsequently, the Persian version of the short-form 12 quality of life questionnaire (SF-12) standardized in former studies was applied to measure the eﬀect of Hefzalsehe instruction on the quality of life of 101 subjects randomly assigned to two demographically-matched groups. Results: Signiﬁcant improvement was observed in physical functioning (19.12 vs. -20.5; P < 0.001), role constraints due to physical problems(42.16vs. -34;P< 0.001),bodilypain(16.67vs. -11;P< 0.001),generalhealth(14.71vs. -12.5;P< 0.001),vitality(12.55vs. -2;P< 0.001), social functioning (18.14 vs. -12; P < 0.001), role constraints due to emotional problems (35.29 vs. -16; P < 0.001), and mental health (14.51 vs. -4.2; P < 0.001) in the experimental group compared with the control group. Conclusions: Thecurrentstudyindicatedpositiveeﬀectsof educationandHefzalseheinstructiononthequalityof lifeparameters.
Variable selection and estimation for high‐dimensional spatial autoregressive models

Spatial regression models are important tools for many scientific disciplines including economics, business, and social science. In this article, we investigate postmodel selection estimators that apply least squares estimation to the model selected by penalized estimation in high‐dimensional regression models with spatial autoregressive errors. We show that by separating the model selection and estimation process, the postmodel selection estimator performs at least as well as the simultaneous variable selection and estimation method in terms of the rate of convergence. Moreover, under perfect model selection, the ℓ2 rate of convergence is the oracle rate of s/n , compared with the convergence rate of slogp/n in the general case. Here, n is the sample size and p, s are the model dimension and number of significant covariates, respectively. We further provide the convergence rate of the estimation error in the form of sup norm, and ideally the rate can reach as fast as logs/n .