Miracle-dz/UniFAR-FTUs huggingface dataset:
Mediated by job satisfaction (Empirical Study: Employees of AirNav Indonesia, Jakarta Air Traffic Services Center Branch)

The purpose of this study is to determine the influence of the work environment and leadership style on employee loyalty with job satisfaction as a mediating variable in AirNav Indonesia, Jakarta Air Traffic Services Center Branch. This study adopts a quantitative approach. The survey was conducted with 180 respondents who met the criteria of being employees of the AirNav Indonesia, Jakarta Air Traffic Services Center Branch. Data were analyzed using Structural Equation Model (SEM) and data processing was carried out using Partial Least Square (PLS) approach with SmartPLS program version 4.0. The results indicate that the variables of work environment, leadership style, and job satisfaction have a positive and significant influence on employee loyalty. In addition, the work environment and leadership style also have a positive and significant influence on job satisfaction. The indirect influence testing results demonstrate that job satisfaction mediates the relationship between the work environment and employee loyalty, as well as mediates the relationship between leadership style and employee loyalty. This research provides practical implications for companies to always pay attention to the work environment and the leadership style employed by their leaders, enabling employees to work in a safe and comfortable environment, thereby enhancing employee loyalty and job satisfaction.
Decision Support System (DSS) for New Student Admissions and Majors by Using Simple Additive Weigthing (SAW) and Fuzzy Tsukomoto at SMA Negeri

Decision support system (DSS) is an information system that helps managers with unique strategic decisions (non-recurring) or a system that provides a means that allows managers to develop information, so that it is appropriate to support the decisions they are making. In this study, the SAW method was used to select student admissions and the Fuzzy Tsukamoto method was used to specialize students. This research is to select and organize specializations so that the school can easily select students and students are not organized in the wrong in specializations. The results of the student selection test using the SAW method, it selected 281 students from 325 students who registered. By using the Fuzzy Tsukamoto method, there were 19 of 281 selected students who were placed in the wrong major. Through a decision support system using the Simple Additive Weighting (SAW) method, criteria are needed to be considered in the selection of new student admissions at SMA 1 Kalirejo. The criteria that have been determined by the school are zoning, non-zoning, and independent.
Petrology of an inverted Barrovian sequence of metapelites in Sikkim Himalaya, India: Constraints on the tectonics of inversion

The lesser Himalayan sequence in Sikkim exposes an unusually complete inverted Barrovian sequence of metapelitic rocks. A number of different bulk compositions are interlayered along the prograde sequence, providing an excellent natural laboratory for studying the controls of pressure, temperature and composition on stability of mineral assemblages. Using three different approaches for determining pressures and temperatures, and making use of the bulk chemical constraints, we show that all three methods yield consistent estimates of pressures and temperatures once the strengths and weaknesses inherent to each approach are critically evaluated. The metamorphic field gradient along two separate traverses are found to be positive (60 °C/kbar in east Sikkim and 70 °C/kbar in north Sikkim) - pressure as well as temperature increases continually up to the highest grade. The various bulk compositions allow different assemblages to be used to establish the coherence of the sequence. In combination these place tight constraints on the permissible tectonic mechanisms for the production of this inverted metamorphic sequence. Neither older hot iron type models, nor more recent models that invoke thrusting (post- or syn- metamorphic) as a mechanism of inversion can produce such a coherent package inverted in pressure as well as temperature. On the other hand, the observations are more consistent with the predictions of channel flow type tectonics. In particular, a recent geodynamic model of subduction-collision that takes into account high heat generation (as found in these Himalayan metapelites) and incorporates the effects of the resulting melting (reduction of viscosity and enhancement of buoyancy) on the tectonic evolution, predicts such inversion of coherent blocks as an unavoidable consequence. Such melting triggered inversion and exhumation as a coherent, fault bounded block explains many features of the inverted sequence in Sikkim and it is not necessary to invoke inversion by multiple thrusting events.
ON THE EFFECT OF CURVATURE AND COMPRESSIBILITY IN LAMINAR BOUNDARY LAYERS OVER FAN BLADES

During the early phases of the turbomachinery design process, it is often the case that various simpliﬁcations and assumptions are made to understand boundary layer behaviour subject to pressure gradients. For example, simpliﬁed boundary-layer models can be employed to appreciate losses incurred in ﬂows over gas turbine components. These neglect the effect of surface curvature and/or density, while retaining the surface pressure distribution. This paper’s objective is to assess the implication of those simpliﬁcations by studying a realistic fan loading and the status of the boundary layer just upstream of a shock. A set of 2D aerofoils, representing the pressure distribution found at 70% and 90% span of a modern low-speed fan, are analysed at cruise conditions. In order to investigate compressibility, the two proﬁles were redesigned to achieve exactly the same pressure loading at incompressible conditions. On the other hand, curvature effects were studied by means of a comparison of incompressible ﬂow over the symmetric aerofoil and a convergent-convergent nozzle, once again with the same loading. The resulting laminar boundary layer quantities were compared explaining the necessary scaling required along with the reasons behind the discrepancies, such as the effect of density and curvature variations. All test-cases were analysed deploying Nektar++. This is a high-order spectral h/p element solver having both compressible and incompressible formulations
EXPLORING POLYPHONIC ACCOMPANIMENT GENERATION USING GENERATIVE ADVERSARIAL NETWORKS

Recently, various neural network architectures have shown capability of achieving compelling results in the ﬁ eld of automatic music generation. Motivated by this, in this work we design a generative framework that is structurally ﬂ exible and adaptable to different musical con ﬁ gurations and practices. At ﬁ rst, we examine the task of multi-track music generation without any human input, by modifying and proposing improvements to the MuseGAN architecture, an established GAN-based system, which we use as our baseline. Afterwards, we extend our developed framework to a cooperative human-AI setup for the generation of polyphonic accompaniments to user-de ﬁ ned tracks. We experiment with multiple structural variants of our model, and two different conditional instruments, namely piano and guitar. For both unconditional and conditional cases, we evaluate the produced samples objectively, using a set of widely used musical metrics, as well as subjectively, by conducting a listening test across 40 subjects. The experimental results, using the Lakh Pianoroll Dataset, reveal that our proposed modi ﬁ cations lead to improvements over the baseline from an auditory perspective in the unconditional case, and also provide useful insights about the properties of the produced music in the conditional setup, depending on the utilized con ﬁ guration.
Map Verification and Repairing Using Formalized Map Specifications

Autonomous vehicles benefit from correct maps to participate in traffic safely, but often maps are not verified before their usage. We address this problem by providing an approach to verify and repair maps automatically based on a formalization of map specifications in higher-order logic. Unlike previous work, we provide a collection of map specifications. We can verify and repair all possible map parts, from geometric to semantic elements, e.g., adjacency relationships, lane types, road boundaries, traffic signs, and intersections. Due to the modular design of our approach, one can integrate additional logics. We compare ontologies, answer set programming, and satisfiability modulo theories with our higher-order logic verification algorithm. Our evaluation shows that our approach can efficiently verify and repair maps from several data sources and of different map sizes. We provide our tool as part of the CommonRoad Scenario Designer toolbox available at commonroad.in. tum.de.
Antifungal Potential of Cladosporium sp. (Endophytic fungi) Associated with Olea europaea L. Leaves

In the leaves of Olea europaea L. Olive trees an endophytic fungus was discovered. Cladosporium sp. was identified to be the fungus based on its morphological characteristics and nuclear ribosomal DNA ITS sequence analysis and was registered in NCBI as the Cladosporium genus has been registered under the number (0P939922.1) The species was not specified, and it was considered of unknown species after comparing it to global isolates. In comparison to olive leaf extract, Cladosporium sp. including total flavonoid, total phenolic, total terpenoid, and total saponins, Which were 121.9%, 198.1%, 89.13%, and 29.87 % respectively compared to its content in olive leaf extract, which was 61.54 %, 67.88 % , 17.1%, and 20.19% respectively. The Cladosporium sp. extract inhibited the growth of 27 isolates belonging to different species of candida which were Candida albicans , C. lypolitica , C. tropicalis , C. sphaerica , C. krusei , C. guilliermondii , C. parapsilosis , C. norvegicus , C. glabrata , and C. kefyr , the inhibition effects increased with increasing concentration to reach the highest level to suppress fungal growth when concentrated 30 mg/ml. This proves the antifungal potential of endophytic fungi in the future.
Using Landsat TM Imagery to Monitor Vegetation Change Following Flow Restoration to the Lower Owens River, California

This Thesis is brought to you for free and open access. It has been accepted for inclusion in Dissertations and Theses by an authorized administrator of PDXScholar. For more information, please contact pdxscholar@pdx.edu. Recommended Citation Bross, Lesley Crandell, "Using Landsat TM Imagery to Monitor Vegetation Change Following Flow Restoration to the Lower Owens River, California" (2015). Dissertations and Theses. Paper 2635.
Tracking unilateral earthquake rupture by P-wave polarization analysis

SUMMARY Rapid estimation of earthquake rupture propagation is essential to declare an early warning for tsunami-generating earthquakes. An increasing number of seismological methods have been developed to determine rupture parameters, such as length, velocity and propagation direction, especially since the occurrence of the Sumatra–Andaman earthquake that resulted in a devastating tsunami in the Indian Ocean region. Here, we present a new method to follow the rupture process in near real time by a polarization analysis of local and regional P phases that permits a faster determination of rupture properties than using teleseismic records. The new technique has the capability to provide detailed information in less than 10 min. Originally, the method stems from a single-station earthquake location method and is expanded here to monitor P-phase polarization variations through time. As the earthquake source moves away from the hypocentre, the backazimuth of an incoming P phase is expected to change accordingly. With polarization analysis we may be able to monitor the temporal change in P-wave backazimuth to follow the rupture process in near real time. Three component P phases are scanned to determine the azimuthal variation as a function of time. The backazimuth of a moving rupture front is determined by the first eigenvector of the covariance matrix. The linearity of the particle motion is used as a measure of the quality of the data. Seismic stations at local and regional distances () are used. We tested the new method with a theoretical simulation and observed seismograms of the Sumatra–Andaman earthquake (2004 December 26, Mw= 9.3), and we were able to follow the rupture for the first 200 s. For larger ruptures, stations at more than 30° epicentral distances would be required. The method is also successfully applied to the Wenchuan earthquake (2008 May 12, Mw= 8.0).
of avian ancestral karyotypes reveals differences in the

Background: Reconstruction of ancestral karyotypes is critical for our understanding of genome evolution, allowing for the identification of the gross changes that shaped extant genomes. The identification of such changes and their time of occurrence can shed light on the biology of each species, clade and their evolutionary history. However, this is impeded by both the fragmented nature of the majority of genome assemblies and the limitations of the available software to work with them. These limitations are particularly apparent in birds, with only 10 chromosome-level assemblies reported thus far. Algorithmic approaches applied to fragmented genome assemblies can nonetheless help define patterns of chromosomal change in defined taxonomic groups. Results: Here, we make use of the DESCHRAMBLER algorithm to perform the first large-scale study of ancestral chromosome structure and evolution in birds. This algorithm allows us to reconstruct the overall genome structure of 14 key nodes of avian evolution from the Avian ancestor to the ancestor of the Estrildidae, Thraupidae and Fringillidae families. Conclusions: Analysis of these reconstructions provides important insights into the variability of rearrangement rates during avian evolution and allows the detection of patterns related to the chromosome distribution of evolutionary breakpoint regions. Moreover, the inclusion of microchromosomes in our reconstructions allows us to provide novel insights into the evolution of these avian chromosomes, specifically.
bacterial microcompartment technology.

Bacterial microcompartments (BMCs) represent proteinaceous macromolecular nano-bioreactors that are found in a broad range of bacteria, and which are associated with either anabolic or catabolic processes. They consist of a semi-permeable outer shell that packages a central metabolic enzyme or pathway, providing both enhanced flux and protection against toxic intermediates. Recombinant production of BMCs has led to their repurposing with the incorporation of altogether new pathways. Deconstruction of BMCs into their component parts has shown that some individual shell proteins self-associate into filaments that can be further modified into a cytoplasmic scaffold to which enzymes/proteins can be targeted. BMCs therefore represent a modular system that is highly suited for the engineering of biological systems for useful purposes.
A Study on the Non-Reconstruction Conjecture in Markov Trees

Consider a d -ary tree T which simulates the process of broadcasting information from the root to other vertices, where each edge is a copy of an irreducible and aperiodic Markov chain M with reversible transition matrix M ∈ R n × n on state space Ω, the goal is to reconstruct the value of the root given values of nodes at level n of the tree, where n → ∞ . This branching process is useful for modeling complex populations that exhibit dependencies between the states of individuals and their ancestors. It can be used to study a wide range of phenomena, including the spread of diseases in populations, the growth of organisms in ecosystems, and the diffusion of information and ideas. We are going to work on the non-reconstruction conjecture of this problem. The conjecture states that information on root cannot be reconstructed if | λ 2 ( M ) | < 1 d , where λ 2 ( M ) is the second largest eigenvalue of M . Our focus is on the scenario where M is symmetric.
Atmospheric deposition of nitrogen and phosphorus in the annual nutrient load of Lake Tahoe (California‐Nevada)

Atmospheric deposition provides most of the dissolved inorganic nitrogen (DIN) and total nitrogen in the annual nutrient load of Lake Tahoe. Deposition also contributes significant amounts of soluble reactive phosphorus (SRP) and total phosphorus loading but plays less of a role than in the case of nitrogen. Most of the DIN probably originates outside of the drainage basin in urban and agricultural areas to the south and west. Spatial patterns of SRP deposition differ from those of DIN and suggest a within-basin terrestrial source, such as leachate from windblown dust or other particles. Because of atmospheric N deposition, the N:P (molar) ratio in combined loading is well above the Redfield ratio of 16 and consistent with an observed shift from colimitation by N and P to persistent P limitation in the lake phytoplankton.
A Case for (Inter)Action: The Role of Log Data in QE

Digital tools have the ability to log the fine-grained details of user experiences within and across the system. These digital experiences can lend valuable contextualization to other ethnographic insights. In this paper, we discuss the potential for using interaction logs as a data source and the pipeline considerations that can facilitate and enhance quantitative ethnographic research using this type of data. We draw on previous QE work and examples from QE adjacent fields such as educational data mining, learning analytics, and human-computer interaction to provide evidence for this approach.
Investigation Related to the Influence of Two Data Parallel Strategies on Pytorch-Based Convolutional Neural Network Model Training

The escalating prevalence of Convolutional Neural Networks (CNNs) coupled with the incessant growth in both model variants and datasets necessitates the formulation of a judicious data parallelism approach to effectively enhance the pace of model training. This imperative arises as a significant challenge confronted by developers and researchers alike. This paper compares data parallelism and distributed data parallelism. Experiments were designed using the CIFAR-10 and VGG16 models. It is found that the training time of multi-GPU adopting data parallel strategy is not ideal. Analyze the reasons for unsatisfactory training time by studying the impact of hardware and hyperparameters on the data parallel strategy. The data path dependence may be the main reason affecting the training time of the data parallel strategy from the unbalanced GPU usage rate when the data parallel strategy is used. The distributed data parallel strategy training model is compared with the data parallel strategy, and the difference between the results of the two is analyzed. Provides advice on the choice of data parallel strategy. The experimental results show that hardware and hyperparameters are not the main reasons for the unsatisfactory training time of the data parallel strategy. Distributed data parallel strategy training time is better than data parallel strategy, but it needs to ensure the accuracy with multiple GPUs.
SUSiNet: See, Understand and Summarize it Petros

In this work we propose a multi-task spatio-temporal network, called SUSiNet, that can jointly tackle the spatio-temporal problems of saliency estimation, action recognition and video summarization. Our approach employs a single network that is jointly end-to-end trained for all tasks with multiple and diverse datasets related to the exploring tasks. The proposed network uses a uniﬁed architecture that includes global and task speciﬁc layer and produces multiple output types, i.e., saliency maps or classiﬁcation labels, by employing the same video input. Moreover, one additional contribution is that the proposed network can be deeply supervised through an attention module that is re-lated to human attention as it is expressed by eye-tracking data. From the extensive evaluation, on seven different datasets, we have observed that the multi-task network performs as well as the state-of-the-art single-task methods (or in some cases better), while it requires less computational budget than having one independent network per each task.
Digital Commons @ New Haven Digital Commons @ New Haven

Preparation of single atom catalysts (SACs) is of broad interest to materials scientists and chemists but remains a formidable challenge. Herein, we develop an ef ﬁ cient approach to synthesize SACs via a precursor-dilution strategy, in which metalloporphyrin (MTPP) with target metals are co-polymerized with diluents (tetraphenylporphyrin, TPP), followed by pyrolysis to N-doped porous carbon supported SACs (M 1 /N-C). Twenty-four different SACs, including noble metals and non-noble metals, are successfully prepared. In addition, the synthesis of a series of catalysts with different surface atom densities, bi-metallic sites, and metal aggregation states are achieved. This approach shows remarkable adjustability and generality, providing suf ﬁ cient freedom to design catalysts at atomic-scale and explore the unique catalytic properties of SACs. As an example, we show that the prepared Pt 1 /N-C exhibits superior chemoselectivity and regioselectivity in hydrogenation. It only converts terminal alkynes to alkenes while keeping other reducible functional groups such as alkenyl, nitro group, and even internal alkyne intact.
Navigating Self-Reﬂection for Aspiring Special Education Teachers: A Scoping Review on Inclusive Educational Practices and Their Insights for Autism Education

: This scoping review investigates the pivotal role of self-reﬂection in enhancing the skills of prospective educators, with the intention of drawing conclusions on how this aspect can contribute to improved teaching for students with autism. Two guiding research questions include: (1) How do targeted strategies in teacher education inﬂuence self-reﬂection among prospective special education teachers, and to what extent do these strategies enhance their reﬂective capacity, as indicated by the reviewed studies? (2) What research gaps exist regarding integrating reﬂective practice into teacher education programs to enhance prospective special education teachers’ self-reﬂection and professionalism? Finally, conclusions drawn from the results are analyzed through the framework of core aspects deﬁned in the ICD-11, the eleventh edition of the ‘International Classiﬁcation of Diseases’. This approach provides insight into how the conclusions can be applied to nurture self-reﬂection of future special education teachers, particularly emphasizing the facilitation of participation and learning for students with autism. Utilizing a scoping review methodology, the study comprehensively explores this vital area, adapting search strategies as needed. Several of the included studies suggested that to effectively contribute to the development of well-considered action strategies in encounters with students in a special education context, including autism education, it is not enough to incorporate reﬂective practice; the teacher candidates also need feedback and guidance. In conclusion, this research underscores self-reﬂection’s pivotal role in bridging theory and practice, enhancing the preparation of future educators for their work with diverse student populations.