Miracle-dz/UniFAR-FTUs huggingface dataset:
Are Valuable and Representative Natural Habitats Sufficiently Protected? Application of Marxan model in the Czech Republic

The joint impact of human activities and climate change on natural resources lead to biodiversity loss. Therefore, it is important to select protected areas through systematic conservation planning. The present study assessed how representative natural habitats are protected under the nature conservation network, and to identify new—but so far insufficiently—protected areas containing these habitats for sustainable management. We used the Marxan model to select the most valuable insufficiently protected natural habitats in the Czech Republic as a representative example for a conservation strategy for Central–Eastern European environments. We set three conservation targets (25%, 50%, and 75%), defining how much percent area of valuable representative natural habitats should be added to the area of the habitats already included in the Nature Protection Network. To implement these conservation targets it is necessary to preserve 22,932 ha, 72,429, ha and 124,363 ha respectively of the conservation targets occurring in the insufficiently protected areas, and 17,255 ha, 51,620 ha, and 84,993 ha respectively of the conservation features in the areas without protection status. Marxan was revealed to be an appropriate tool to select the most valuable and insufficiently protected natural habitats for sustainable management.
Inverse driver learning and short time prediction in freeway traffic situations

Traffic prediction around the vehicle during highway driving is a hard task to solve as the driver’s decision are complicated. It is necessary to build a procedure to predict driving decisions, such as lane change, overtaking and many other scenarios around the vehicle. Further, building an accurate prediction model is a requisite to improve the design and validation of Automated Driving Systems (ADS). To solve the prediction task, the project aims to build a Deep Inverse Reinforcement Learning (DIRL) model to analyze and learn diverse driving behaviour during lane change scenarios. DIRL learns this behaviour by undergoing apprenticeship training from an expert. It learns the reward structure of drivers decision during lane change scenarios from such varied expert driving behaviour, and by utilizing these reward it predicts driving decision. DIRL model is built upon a sequential time series model and General Adversarial Imitation Learning (GAIL). GAIL assists in learning the rewards and future trajectories are predicted using the sequential model. The model is optimized using reinforcement learning techniques by performing policy gradients on the rewards, that are obtained from the GAIL. The model is trained on expert naturalistic driving data recorded on German highways called HighD. The model predicts lateral, longitudinal position and velocity of surrounding vehicles. The accuracy of these predictions is evaluated by comparing these trajectories with expert data.
The Effect of Earthquake Frequency Content on the Internal Forces in the Tunnels Permanent Lining

ABSTRACT In this paper, the effect of earthquake frequency content on the tunnel permanent lining is studied. For this purpose, dynamic analysis of Gilavand tunnel was performed using 15 real accelerograms with different frequency contents by the finite difference method (FDM). Although accelerograms have the same maximum acceleration and duration, they are different in predominant frequency, peak particle velocity (PPV), peak particle displacement (PPD), and specific energy density (SED). The results showed that the closer the frequency of earthquakes to the ground natural frequency, the larger the forces and displacement in tunnel lining.
Differentiating between integration and non-integration strategies in perceptual decision making

Many tasks used to study decision-making encourage subjects to integrate evidence over time. Such tasks are useful to understand how the brain operates on multiple samples of information over prolonged timescales, but only if subjects actually integrate evidence to form their decisions. We explored the behavioral observations that corroborate evidence-integration in a number of task-designs. Several commonly accepted signs of integration were also predicted by non-integration strategies. Furthermore, an integration model could fit data generated by non-integration models. We identified the features of non-integration models that allowed them to mimic integration and used these insights to design a motion discrimination task that disentangled the models. In human subjects performing the task, we falsified a non-integration strategy in each and confirmed prolonged integration in all but one subject. The findings illustrate the difficulty of identifying a decision-maker’s strategy and support solutions to achieve this goal.
Wide‐gap (Ag,Cu)(In,Ga)Se2 solar cells with different buffer materials—A path to a better heterojunction

This contribution concerns the effect of the Ag content in wide‐gap AgwCu1‐wIn1‐xGaxSe2 (ACIGS) absorber films and its impact on solar cell performance. First‐principles calculations are conducted, predicting trends in absorber band gap energy (Eg) and band structure across the entire compositional range (w and x). It is revealed that a detrimental negative conduction band offset (CBO) with a CdS buffer can be avoided for all possible absorber band gap values (Eg = 1.0–1.8 eV) by adjusting the Ag alloying level. This opens a new path to reduce interface recombination in wide‐gap chalcopyrite solar cells. Indeed, corresponding samples show a clear increase in open‐circuit voltage (VOC) if a positive CBO is created by sufficient Ag addition. A further extension of the beneficial compositional range (positive CBO at buffer/ACIGS interface) is possible when exchanging CdS with Zn1‐ySnyOz, because of its lower electron affinity (χ). Nevertheless, the experimental results strongly suggest that at present, residual interface recombination still limits the performance of solar cells with optimized CBO, which show an efficiency of up to 15.1% for an absorber band gap of Eg = 1.45 eV.
The KEY for chemo-immunotherapy combination: taking NOTEs from squamous cell lung cancer

Lung cancer represents the most common cause of cancer death in the world. Non-small cell lung cancer (NSCLC) represents almost 85% of lung cancer cases. Unfortunately, diagnosis is often made at advanced or metastatic stage, with a 5-year survival rate between 0 and 5% with chemotherapy, that until a few years ago represented the only systemic treatment available (1,2). In this context, the primary goal of systemic therapy is to increase patients’ survival, to reduce cancer symptom burden and to improve quality of life. Over the past decade, together with the availability of targeted agents in oncogene-addicted cases, the development of immune checkpoint inhibitors, namely monoclonal antibodies anti-programmed death-1 (PD-1) and its ligand (PD-L1), has revolutionized the treatment of advanced NSCLC, establishing a new era in the treatment of lung cancer patients. Their efficacy has been demonstrated, initially, as second line therapy in patients affected by advanced, EGFR wild type and ALK not rearranged NSCLC, after a previous platinum-based chemotherapy. Afterwards, the efficacy of these drugs in the first-line setting has been explored: the randomized phase III study KEYNOTE-024, conducted in NSCLC patients with tumors characterized by PD-L1 expression equal to or higher than 50%, demonstrated that pembrolizumab is associated with a better outcome compared to standard platinum-based chemotherapy, in terms of both progressionfree survival (PFS) and overall survival (OS), getting the approval in this setting by regulatory agencies (3). Consequently, the determination of PD-L1 has become part of the baseline diagnostic evaluation, representing an important biomarker for the first-line patients’ selection, although with the well-known limitations in both positive and negative predictive value. Nevertheless, cases characterized by a PD-L1 expression equal to or higher than 50% represent just a minority (20– 30%) of the entire population (4). In order to expand the potentia l benef i t from immunotherapy to a larger number of patients, several phase 3 studies combining the potential immunogenic effect of chemotherapy with PD-(L)1 blockade have emerged in rapid succession with positive results. For instance, the KEYNOTE-189 trial showed a significantly longer OS and PFS compared with chemotherapy alone in untreated advanced nonsquamous NSCLC patients (5).
Leveraged Trading, Irrational Sentiment and Sustainability in the Stock Market: Evidence from China

Leveraged trading exhibits the characteristics of “strong margin trading and weak short selling” in the Chinese stock market. On the basis of monthly data on leveraged trading in the Chinese stock market from January 2014 to December 2016, we aim to empirically examine the relationship between leveraged trading and investor sentiment, and analyze the characteristics of investor sentiment contained in the leverage ratio. The results show that (1) as the leverage ratio increases, the pattern of investor trading changes from the positive feedback trading of “chasing up and down” to the negative feedback trading of “selling high and buying low”; (2) leveraged trading has the typical characteristics of irrational sentiment; (3) inverse arbitrage strategies based on leverage ratios is effective in one month in the Chinese market. The findings in this paper provide empirical support for clarifying the influence mechanism between leveraged trading and investor sentiment, and can serve as a useful reference for reducing the impact of leveraged trading on volatility and maintaining the sustainability of the stock market.
Data Dashboard for Decision Support Systems for Intrapreneurship in A Company

Nowadays, as the Information and Technology rapidly growing all across the world, Indonesia as one of many developed countries always tries to keep up relating to this trend. Regarding to this situation, the use of Information and Technology in various fields are greatly enhanced, and not to mention businesses. There are a lot of businesses using technology, building a start-up is one of the common ways to combine technology with innovation. Intrapreneurship is a media to develop new venture within an organization and to exploit new opportunities. To help the continuity of entrepreneurship, there must be an Innovation Management that serves help to develop ideas from the internal employees and always find the best solution to help the intrapreneurs grows in the best environment. To make a better decision making, management need some tools to monitor and evaluate the Intrapreneurs. Data Dashboard aims to help the decision maker to see the Intrapreneurs’ performance and at once feel their pain and gain. With those insights that can be obtained from the dashboard, hopefully, management can get enough information to make the best decision regarding the continuity status of each Intrapreneurs. This research will provide the dashboard with some algorithm to show the recommendation data about the status of Intrapreneurs.
A tornado daily impacts simulator for the central and southern United States

In an average year (1979–2016), the United States experiences nearly 1,100 tornadoes, which cause a total of 68 fatalities. Annual fatality rates have decreased since the peak in the 1920s, but there is a concern that they could start to rise again with increases in vulnerable populations and the impacts of climate change. It is possible to assess the risk of tornado fatalities using the historical record. However, the rarity of tornadoes and the short period of record may not capture the true risk. One way around this problem is to simulate thousands of years’ worth of tornadoes to obtain a broader picture of risk. Previous tornado risk models have distributed tornadoes randomly or used climatology to generate realistic tornado patterns on an annual (or longer) time scale. From an operational standpoint, it would be useful to have a model that distributes tornadoes on a daily time step to enable the forecasting of potential tornado impacts on a given day. The present study introduces one such model that distributes tornadoes using information about the favourability of the atmospheric environment for tornado development: The Tornado Daily Impacts Simulator (TorDIS). The paper demonstrates model utility through 1,000 year simulations over several metropolitan areas and with a comparison between modelled and observed impacts for several high‐impact tornado days. Forecasting potential tornado impacts on a daily time step could allow emergency managers to plan ahead for high‐risk days to prioritize their resources and save lives.
Distribution-controlled and optimally spread non-Cartesian sampling curves for accelerated in vivo brain imaging at 7 Tesla

This work reports the use of new non-Cartesian k-space trajectories whose improved efficiency allows to significantly reduce MR scan time with minimum deterioration of image quality. Instead of using simple geometrical patterns, we introduce an approach inspired from stippling techniques, which automatically designs optimized sampling patterns along any distribution by taking full advantage of the hardware capabilities. Our strategy leads to drastically accelerated acquisitions, as demonstrated by our experimental results at 7T on in vivo human brains. We compare our method to widely-used non-Cartesian trajectories (spiral,radial) and demonstrate its superiority regarding image quality and robustness to system imperfections.
PENINGKATAN KOMPETENSI PROFESIONAL DAN PEDAGOGIK GURU SMA DI PROVINSI JAMBI

Guru merupakan komponen paling menentukan dalam sistem pendidikan yang harus mendapat perhatian utama. Tujuan Penelitian ini adalah untuk mengetahui Kompetensi Professional dan Pedagogik guru SMA di Provinsi Jambi serta untuk mengetahui kendala-kendala yang dialami guru dalam meningkatkan kompetensi tersebut. Penelitian ini menggunakan metode campuran (mixed methods). Teknik pengambilan sampel dalam penelitian ini adalah purposive. Sampel penelitian dipilih berdasarkan nilai Uji Kompetensi Guru dengan kriteria nilai tertinggi, menengah dan terendah. Hasil penelitian menunjukan bahwa Rata-rata pemahaman kompetensi profesional guru di tiga sampel penelitian dengan skor rata-rata 84,2 %, dan kompetensi pedagogik dengan skor rata-rata 81,4 %. Adapun kendala yang dihadapi oleh guru SMA di Provinsi Jambi adalah minimnya metode dan variasi guru dalam pengajaran, belum memadainya sarana penunjang pembelajaran, masih minimnya pemanfaatan teknologi dan informasi dalam proses pembelajaran, kurangnya pelatihan, optimalisasi Musyawarah Guru Mata Pelajaran (MGMP) dan kurangnya apresiasi terhadap guru yang kreatif dan berprestasi. Untuk itu pemerintah melalui Dinas Pendidikan Provinsi Jambi agar dapat menyediakan pelatihan bagi guru yang langsung menyentuh aspek desain pembelajaran, keterampilan menggunakan alat pembelajaran yang berbasis teknologi dan informasi. Selain itu, peran MGMP perlu ditingkatkan melalui kegiatan menyediakan pembinaan yang professional (tutor) yang dapat membimbing dan membantu guru dalam meningkatkan kinerja dan kompetensi.
What’s in a word? The importance of the concept of “values” in the prevention of abuse of older people in care homes

Purpose The purpose of this paper is to present some of the findings from an empirical, mixed methods research project that reveal the importance of the personal value frameworks held by individual staff in the prevention of abuse of older people in private sector care homes. Design/methodology/approach Semi-structured interviews were undertaken with a sample of 36 care home personnel, including proprietors, care managers and care staff. Findings A significant number of respondents identified the importance of personal value frameworks among staff providing care as a potential contributory factor in the prevention of abuse of older people. Research limitations/implications Though the research draws upon the experiences of only 36 care home personnel through interviews, data suggest that the personal evaluations of staff towards those in their care is a significant contributory factor to the occurrence of abuse. Originality/value The research has identified individual staff value frameworks as a causal factor in the occurrence of abuse. The research also confirms that the perceptions of “values” among respondents directly involved in the provision of care are at odds with common understanding of “values” often cited elsewhere in connection with staff recruitment and training as a means of preventing the occurrence of abuse.
Drivers of plant traits that allow survival in wetlands

Plants have developed a suite of traits to survive the anaerobic and anoxic soil conditions in wetlands. Previous studies on wetland plant adaptive traits have focused mainly on physiological aspects under experimental conditions, or compared the trait expression of the local species pool. Thus, a comprehensive analysis of potential factors driving wetland plant adaptive traits under natural environmental conditions is still missing.In this study, we analysed three important wetland adaptive traits, i.e. root porosity, root/shoot ratio and underwater photosynthetic rate, to explore driving factors using a newly compiled dataset of wetland plants. Based on 21 studies at 38 sites across different biomes, we found that root porosity was affected by an interaction of temperature and hydrological regime; root:shoot ratio was affected by temperature, precipitation and habitat type; and underwater photosynthetic rate was affected by precipitation and life form. This suggests that a variety of driving mechanisms affect the expression of different adaptive traits.The quantitative relationships we observed between the adaptive traits and their driving factors will be a useful reference for future global methane and denitrification modelling studies. Our results also stress that besides the traditionally emphasized hydrological driving factors, other factors at several spatial scales should also be taken into consideration in the context of future functional wetland ecology.
Fixed-Term Work Contracts and Anti-Immigration Attitudes. A Novel Test of Ethnic Competition Theory

Whether labor market competition is shaping anti-immigration attitudes is a contentious issue. We conduct a novel test of ethnic competition theory by comparing the attitudes towards immigration of workers with fixed-term contracts to those with permanent jobs in Europe. Fixed-term contract workers are particularly at risk of competition as they have to compete for jobs in the foreseeable future. In the first step of our investigation, we analyze cross-sectional data (ESS, 2002–18) from 18 Western European countries. We find that—contrary to our expectation—fixed-term workers are less anti-immigration. The effect is substantively small. In the second step, we use a fixed-effects design with longitudinal data from the German Socio-Economic Panel (GSOEP, 1999–2015) to rule out time-constant unobserved heterogeneity. We find that transitioning from a fixed- to a permanent contract does not affect anti-immigration attitudes. Our combined results thus add to the evidence against labor market competition as an explanation of anti-immigrant attitudes.
Independent tasks on 2 resources with co-scheduling effects

Concurrent kernel execution is a relatively new feature in modern GPUs, which was designed to improve hardware utilization and the overall system throughput. However, the decision on the simultaneous execution of tasks is performed by the hardware with a leftover policy, that assigns as many resources as possible for one task and then assigns the remaining resources to the next task. This can lead to unreasonable use of resources. In this work, we tackle the problem of co-scheduling for GPUs with and without preemption, with the focus on determining the kernels submission order to reduce the number of preemptions and the kernels makespan, respectively. We propose a graph-based theoretical model to build preemptive and non-preemptive schedules. We show that the optimal preemptive makespan can be computed by solving a Linear Program in polynomial time, and we propose an algorithm based on this solution which minimizes the number of preemptions. We also propose an algorithm that transforms a preemptive solution of optimal makespan into a non-preemptive solution with the smallest possible preemption overhead. We show, however, that finding the minimal amount of preemptions among all preemptive solutions of optimal makespan is a NP-hard problem, and computing the optimal non-preemptive schedule is also NP-hard. In addition, we study the non-preemptive problem, without searching first for a good preemptive solution, and present a Mixed Integer Linear Program solution to this problem. We performed experiments on real-world GPU applications and our approach can achieve optimal makespan by preempting 6 to 9% of the tasks. Our non-preemptive approach, on the other side, obtains makespan within 2.5% of the optimal preemptive schedules, while previous approaches exceed the preemptive makespan by 5 to 12%.
Passive Re-colonization of the Spider Assemblage on an Ohio Restored Tall Grass Prairie Compared to Nearby Remnant Prairies and Old Fields

The reconstructed prairie on the Marion Campus of The Ohio State University was established in 1977. Since then restoration has focused on plants. Animals on the site have recolonized without active management. Spider assemblages were sampled in 2000 and compared to those sampled at the time on 2 remnant prairies and 2 old fields. Pitfall traps and sweep nets were used for sampling. In 2000, spiders (n = 1,541) representing 94 species were captured; 91% of these were captured with pitfall traps. The restored Marion Campus Prairie was inhabited by an assemblage of spiders resembling those on nearby remnant prairies and old fields.
Comparative Evaluation of Coronally Advanced Flap Using Platelet-rich Fibrin Membrane and Fresh Amniotic Membrane in Gingival Recession

Background: the aim of this study was to evaluate and compare the effectiveness of root coverage with coronally advanced flap combined with Platelet Rich Fibrin or Fresh Amniotic Membrane. Materials and Methods: thirty patients had Miller class I or II in maxillary anterior teeth were involved in the present study. Each recession defect was randomly assigned to one of the treating groups: coronally advanced flap with Platelet rich fibrin (PRF group) and coronally advanced flap with fresh amniotic membrane (AM) (AM Group). Clinical measurements of recession depth (RD), root coverage percentage (RC%) pocket depth (PD), clinical attachment level (CAL) and width of keratinized tissue (WKT) were evaluated at the baseline, three months, six months and nine months postoperatively. Statistical analysis was performed for intergroup and intragroup comparisons respectively. Results: intragroup comparison displayed statistical significant difference with regard to RD and CAL at different time interval. No statistical significant difference between groups at different time interval with regard to RD, PD, CAL while WKT, AM group demonstrated statistical significant increase compared to PRF group. Conclusion: Both the membranes provided successful and predictable root coverage when combined with CAF. AM was more effective in terms of increase in WKT.