Miracle-dz/UniFAR-FTUs huggingface dataset:
Academic Libraries and the Pandemic

Abstract In the spring of 2020, many academic libraries and librarians transitioned their service models due to the pandemic and societal changes. Since then, an evolving and changing practice for providing library services to the academic community has begun. After a return to physical spaces, academic libraries have started to provide new in-person services, such as makerspaces. Some of the library services that were added during the height of the pandemic, continue on presently. How has this affected academic libraries and staff? The article will focus on what academic libraries have learned from the organizational culture and EDI perspectives, with particular attention to what has occurred since 2020. A literature review will also discuss the similarities or differences among academic libraries worldwide. Have academic libraries reflected sufficiently to enhance their services?
Comparison of application of various crossovers in solving inhomogeneous minimax problem modified by Goldberg model

This paper considers one of the classical NP complete problems - an inhomogeneous minimax problem. When solving such large-scale problem, there appear difficulties in obtaining an exact solution. Therefore, let us propose getting an optimum solution in an acceptable time. Among a wide range of genetic algorithm models, let us choose the modified Goldberg model, which earlier was successfully used by authors in solving NP complete problems. The classical Goldberg model uses a single-point crossover and a singlepoint mutation, which somewhat decreases the accuracy of the obtained results. In the article, let us propose using a full two-point crossover with various mutations previously researched. In addition, the work studied the necessary probability to apply it to the crossover in order to obtain results that are more accurate. Results of the computation experiment showed that the higher the probability of a crossover, the higher the quality of both the average results and the best solutions. In addition, it was found out that the higher the values of the number of individuals and the number of repetitions, the closer both the average results and the best solutions to the optimum. The paper shows how the use of a full two-point crossover increases the accuracy of solving an inhomogeneous minimax problem, while the time for getting the solution increases, but remains polynomial.
A new methodology for an adaptive state observer design for a class of nonlinear systems with unknown parameters in unmeasured state dynamics

An adaptive state observer is an adaptive observer that does not require the persistent excitation condition to estimate the state. The usual structural requirement for designing this kind of observers is that the unknown parameters explicitly appear in the measured state dynamics. This paper deals with the problem of adaptive state observer synthesis for a class of nonlinear systems with unknown parameters in unmeasured state dynamics. The novelty of the proposed approach is that it requires neither a canonical form nor the approximation of some of the output’s time derivatives. Firstly, we establish a new matrix equality that characterizes the structure of almost all systems found in the very small literature dealing with this problem. Then, this equality is exploited in the construction of the adaptation law. This simplifies the design procedure and makes it very similar to the conventional adaptive state observer design procedure. The problem of finding the observer gains is expressed as a linear matrix inequalities optimization problem. Two examples are given to demonstrate the validity of the proposed scheme.
Transcriptomic analysis reveals transcription factors involved in vascular bundle development and tissue maturation in ginger rhizomes (Zingiber officinale Roscoe)

Ginger (Zingiber officinale Roscoe) is an important vegetable with medicinal value. Rhizome development determines ginger yield and quality. However, little information is available about the molecular features underlying rhizome expansion and maturation. In this study, we investigated anatomy characteristics, lignin accumulation and transcriptome profiles during rhizome development. In young rhizomes, the vascular bundle (VB) was generated with only vessels in it, whereas in matured rhizomes, three to five layers of fibre bundle in the xylem were formed, resulting in VB enlargement. It indicates VB development favouring rhizome swelling. With rhizome matured, the lignin content was remarkably elevated, thus facilitating tissue lignification. To explore the regulators for rhizome development, nine libraries including ginger young rhizomes (GYR), growing rhizomes (GGR), and matured rhizomes (GMR) were established for RNA-Seq, a total of 1264 transcription factors (TFs) were identified. Among them, 35, 116, and 14 differentially expressed TFs were obtained between GYR and GGR, GYR and GMR, and GGR and GMR, respectively. These TFs were further divided into three categories. Among them, three ZobHLHs (homologs of Arabidopsis LHW and AtbHLH096) as well as one DIVARICATA homolog in ginger might play crucial roles in controlling VB development. Four ZoWRKYs and two ZoNACs might be potential regulators associated with rhizome maturation. Three ZoAP2/ERFs and one ZoARF might participate in rhizome development via hormone signalling. This result provides a molecular basis for rhizome expansion and maturation in ginger.
Alzheimer Disease Diagnosis using the K-means, GLCM and K_NN

البحث في الصور الطبية له الاثر الكبير في حقل العلاج. في هذا البحث، تم استخدام صور الرنين المغناطيسي لتمييز الدماغ الطبيعي من الدماغ المصاب بمرض الزهايمر . النسيج(texture) هو الخاصية الأهم حيث يحتوي على حقائق هامة حول التنظيم الهيكلي اللاسطح وصلاته بالمنطق المجاورة للنسيج. في حقل تصنيف النسيج يجب أن يكون مقسمه إلى عدد من المناطق التي تتشارك الخصائص، لهذا الغرض استخدمنا خوارزمية k- means مع GLCM لاستخراج الخصائص، وأخيرا استخدمنا خوارزمية k-nearest neighbor للتمييز بين الدماغ طبيعي وغير طبيعي
Immediate schedule adjustment and semidefinite relaxation

This paper considers the problem of temporary shortage of some resources within a project execution period. Mathematical models for two different cases of this problem are established. Semidefinite relaxation technique is applied to get immediate solvent of these models. Relationship between the models and their semidefinite relaxations is studied, and some numerical experiments are implemented, which show that these mathematical models are reasonable and feasible for practice, and semidefinite relaxation can efficiently solve the problem.
The Simple Algebra of Surplus in Open, Private Values Auctions: A Nested Logit Merger Model

In a private values, open auction, we show that bidder surplus can be expressed as a simple difference between unconditional moments of order statistics. The strength of the result is its simplicity and generality, as we dispense with the typical assumptions of independence and/or symmetry. We show how to use the expression to derive closed-form expressions for the effects of a merger among bidders for any joint value distribution, and illustrate its use by simulating the effects of the 2016 proposed Anthem-Cigna merger using a nested logit specification.
Survey-scale discovery-based research processes: Evaluating a bespoke visualisation environment for astronomical survey data

Abstract Next-generation astronomical surveys naturally pose challenges for human-centred visualisation and analysis workflows that currently rely on the use of standard desktop display environments. While a significant fraction of the data preparation and analysis will be taken care of by automated pipelines, crucial steps of knowledge discovery can still only be achieved through various level of human interpretation. As the number of sources in a survey grows, there is need to both modify and simplify repetitive visualisation processes that need to be completed for each source. As tasks such as per-source quality control, candidate rejection, and morphological classification all share a single instruction, multiple data (SIMD) work pattern, they are amenable to a parallel solution. Selecting extragalactic neutral hydrogen (Hi) surveys as a representative example, we use system performance benchmarking and the visual data and reasoning methodology from the field of information visualisation to evaluate a bespoke comparative visualisation environment: the encube visual analytics framework deployed on the 83 Megapixel Swinburne Discovery Wall. Through benchmarking using spectral cube data from existing Hi surveys, we are able to perform interactive comparative visualisation via texture-based volume rendering of 180 three-dimensional (3D) data cubes at a time. The time to load a configuration of spectral cubes scale linearly with the number of voxels, with independent samples of 180 cubes (8.4 Gigavoxels or 34 Gigabytes) each loading in under 5 min. We show that parallel comparative inspection is a productive and time-saving technique which can reduce the time taken to complete SIMD-style visual tasks currently performed at the desktop by at least two orders of magnitude, potentially rendering some labour-intensive desktop-based workflows obsolete.
Broadband 1 x 4 Silicon Nitride Photonic Switch Fabricated on a Hybrid Electrothermal and Electrostatic MEMS Platform

This study demonstrates a monolithic 1 x 4 optical switch composed of a planar micro-electro-mechanical system (MEMS) integrated with silicon nitride (SiN) waveguides. The switching motion is induced by an optimized cascaded chevron electrothermal actuator, which produces an analog, precise, and large stroke for low voltages. Nanoscale displacement measurements show a repeatability on the order of 10 nm and a total switching displacement of ∼12 μm for about 10 V. To reduce the insertion losses, a parallel plate electrostatic actuator closes the gap between the waveguides after the switching motion. The optical transmission, measured for 10 devices, is roughly the same across the entire 1520--1620 nm wavelength range. The average optical losses are 4.0 ± 1.9, 4.4 ± 2.0, 4.9 ± 1.9, and 4.1 ± 1.2 dB for ports 1 to 4 respectively, while the average optical crosstalk is smaller than −35 dB. The relatively compact switch (< 1 mm2), considering its large displacement, is built on a silicon-on-insulator wafer with a customized fabrication process flow developed by AEPONYX Inc. We believe that this device can lead the way to a new class of small and robust MEMS integrated silicon photonic devices able to operate over a wide wavelength span and to provide a large tuning range for low voltages. Future work will focus on reducing the switch optical losses and on achieving near zero power consumption with the addition of mechanical latches.
Structural Transitions of Papain-like Cysteine Proteases: Implications for Sensor Development

The significant role of papain-like cysteine proteases, including papain, cathepsin L and SARS-CoV-2 PLpro, in biomedicine and biotechnology makes them interesting model systems for sensor development. These enzymes have a free thiol group that is suitable for many sensor designs including strong binding to gold nanoparticles or low-molecular-weight inhibitors. Focusing on the importance of the preservation of native protein structure for inhibitor-binding and molecular-imprinting, which has been applied in some efficient examples of sensor development, the aim of this work was to examine the effects of the free-thiol-group’s reversible blocking on papain denaturation that is the basis of its activity loss and aggregation. To utilize biophysical methods common in protein structural transitions characterization, such as fluorimetry and high-resolution infrared spectroscopy, low-molecular-weight electrophilic thiol blocking reagent S-Methyl methanethiosulfonate (MMTS) was used in solution. MMTS binding led to a two-fold increase in 8-Anilinonaphthalene-1-sulfonic acid fluorescence, indicating increased hydrophobic residue exposure. A more in-depth analysis showed significant transitions on the secondary structure level upon MMTS binding, mostly characterized by the lowered content of α-helices and unordered structures (either for approximately one third), and the increase in aggregation-specific β-sheets (from 25 to 52%) in a dose-dependant manner. The recovery of this inhibited protein showed that reversibility of inhibition is accompanied by reversibility of protein denaturation. Nevertheless, a 100-fold molar excess of the inhibitor led to the incomplete recovery of proteolytic activity, which can be explained by irreversible denaturation. The structural stability of the C-terminal β-sheet rich domain of the papain-like cysteine protease family opens up an interesting possibility to use its foldamers as a strategy for sensor development and other multiple potential applications that rely on the great commercial value of papain-like cysteine proteases.
Improvement of the quality management system of industrial enterprises based on the use of corporate knowledge

This article analyzes the procedures for improving quality management using the example of solving problems of compliance with product quality requirements at industrial enterprises. The quality of the products largely depends on the use of modern methods and tools of quality management, as well as on improving the competence of personnel in the field of quality systems. In this regard, it is proposed to apply the corporate knowledge of the enterprise, including models and algorithms of artificial intelligence. Corporate knowledge is formed on the basis of the formation and processing of documentation, interviewing qualified specialists and intellectual data analysis on the implementation of business processes. During the research, an ontology of quality management was developed, decision-making rules were created and the results of improving the quality management system using a neuro-fuzzy network were predicted. The use of these artificial intelligence tools will make it possible to form a unified terminology to ensure an unambiguous perception of information by all participants in the process and the use of a knowledge base to support decisionmaking. It is proposed to use quality management tools to improve the efficiency of decisions made by intelligent tools, i.e. production rules and neural networks.
An Error Bound for Low Order Approximation of Dynamical Systems Subjected to Initial Conditions

In recent years, a great effort has been taken focused on the development of reduced order modeling techniques of dynamical systems. This necessity is pushed by the requirement for efficient numerical techniques for simulations of dynamical systems arising from structural dynamics, controller design, circuit simulation, fluid dynamics and micro electromechanical systems.We introduce a method to calculate the minimum upper $\mathcal{L}_2$ error bound of a linear time invaritant reduced order model considering any possible unitary initial conditions (IC). As a consequence, the proposed method calculates the unitary IC vector which leads to the maximum $\mathcal{L}_2$ norm of the error. Based on this error bound, it is discussed the capacity of a reduced order system to approximate the free transient response in the worst case scenario.
How Gaussian mixture models might miss detecting factors that impact growth patterns

Longitudinal studies play a prominent role in biological, social, and behavioral sciences. Repeated measurements over time facilitate the study of an outcome level, how individuals change over time, and the factors that may impact either or both. A standard approach to modeling childhood growth over time is to use multilevel or mixed effects models to study factors that might play a role in the level and growth over time. However, there has been increased interest in using mixture models, which have inherent grouping structure to more flexibly explain heterogeneity in the longitudinal outcomes, to study growth patterns. While several possible model specifications can be used, these methods generally fail to explicitly group individuals by the shape of their growth pattern separate from level, and thus fail to shed light on the relationships between growth pattern and potential explanatory factors. We illustrate the weaknesses of these methods as they are currently being used. We also propose a pre-processing step that removes the outcome level to focus explicitly on shape, discuss its impact on estimation, and demonstrate its usefulness though a simulation study and with real longitudinal data.
Approximation Algorithms for Effective Team Formation

Approximation Algorithms for Effective Team Formation by George Rabanca Advisor: Professor Amotz Bar-Noy This dissertation investigates the problem of creating multiple disjoint teams of maximum efficacy from a fixed set of workers. We identify three parameters which directly correlate to the team effectiveness – team expertise, team cohesion and team size – and propose efficient algorithms for optimizing each in various settings. We show that under standard assumptions the problems we explore are not optimally solvable in polynomial time, and thus we focus on developing efficient algorithms with guaranteed worst case approximation bounds. First, we investigate maximizing team expertise in a setting where each worker has different expertise for each job and each job may be completed only by teams of certain sizes. Second, we consider the problem of maximizing team cohesion when the set of workers form a social network with known pairwise compatibility. Third, we explore the problem from a game theoretic perspective in which multiple teams compete on a fixed number of workers and the true needs of each team are private. We present allocation algorithms that both incentivize teams to state their needs accurately and allocate workers effectively. Finally, we experimentally measure the correlation between team cohesiveness, team expertise and team efficacy on a social network graph of computer science research co-authorship.
Three-dimensional flow past a fixed or freely vibrating cylinder in the early turbulent regime

The three-dimensional structure of the flow downstream of a circular cylinder, either fixed or subjected to vortex-induced vibrations, is investigated by means of numerical simulation, at Reynolds number 3900, based on the cylinder diameter and current velocity. The flow exhibits pronounced fluctuations distributed along the span in all studied cases. Qualitatively, it is characterized by spanwise undulations of the shear layers separating from the body and the development of vortices elongated in the plane normal to its axis (planar vortices). A quantitative analysis of crossflow vorticity fluctuations in the spanwise direction reveals a peak of fluctuation amplitude in the near region (i.e., area of formation of the spanwise wake vortices) and opposite trends of the spanwise wavelength in the shear layer and wake regions; the wavelength tends to decrease as a function of the streamwise distance in the shear layers down to a minimum value close to 0.5 body diameters and then slowly increases further in the wake. The spanwise structure of the flow is differently altered in these two regions, once the cylinder vibrates. In the shear layer region, body motion is associated with an enhancement of planar vortex formation. The amplification of vorticity spanwise fluctuations in this region is accompanied by a reduction of the spanwise wavelength; it is found to decrease as a function of the instantaneous Reynolds number based on the instantaneous flow velocity seen by the moving body, following the global trend of the wavelength versus Reynolds number previously reported for fixed cylinders. In the wake region, the flow spanwise structure is essentially unaltered compared to the fixed body case, in spite of the major distortions of the streamwise and crossflow length scales.
Extensions and Applications of Multilevel and Multidimensional Item Response Models

Author(s): Choi, In Hee | Advisor(s): Wilson, Mark | Abstract: Multilevel and multidimensional item response models are two commonly used examples as extensions of the conventional item response models. In this dissertation, I investigate extensions and applications of multilevel and multidimensional item response models, with a primary focus on longitudinal item response data that include students' school switching, classification of examinees into latent classes based on multidimensional aspects, and measurement models for complicated learning progressions. In the first paper, multilevel item response models for longitudinal data are extended to the crossed-classified models (Rasbash a Goldstein, 1994; Raudenbush, 1993) and multiple membership models (Hill a Goldstein, 1998; Rasbash a Browne, 2001) to incorporate students' school mobility. If students switch school over time in longitudinal studies, the data structure is not strictly hierarchical; therefore, conventional multilevel models are not applicable. In this study, two types of school mobility and corresponding models are specified. Furthermore, this study investigates the impacts of misspecification of school membership in the analysis of longitudinal data. In the second and third paper, mixture models and measurement models based on multidimensional item response models are presented respectively. The second paper investigates possible usefulness of the mixture random weights linear logistic test model (MixRWLLTM) as a means to identify subgroups of examinees as well as to improve interpretations of differences between latent classes. In the proposed MixRWLLTM, examinees are classified with respect to their multidimensional aspects, a general propensity (intercept) and random coefficients of the item properties. In the third paper, a structured constructs model (SCM) for the continuous latent trait is developed to deal with complicated learning progressions, in which relations between levels across multiple constructs are assumed in advance. Based on the multidimensional Rasch model, discontinuity parameters are incorporated to model the hypothesized relations as the advantage or disadvantage for respondents belonging into a certain level in one construct to reach a level in another construct.
Clustering of child deaths among families in low and middle‐income countries: A meta‐analysis

Several studies have examined the phenomenon of “death clustering,” in which two or more children born to the same mother or from the same family die at an early age. Therefore, a scientific examination of the results is essential to understand how the survival status of the older siblings affects the survival of the younger siblings. By using meta‐analysis, this study aims to provide a quantitative synthesis of the results of studies on “child death clustering” in low‐ and middle‐income countries (LMICs).
Advanced tokamak investigations in full-tungsten ASDEX Upgrade

The appropriate tailoring of the q-profile is the key to accessing Advanced Tokamak (AT) scenarios, which are of great benefit to future all-metal fusion power plants. Such scenarios depend on low collisionality ν* which permits efficient external current drive and high amounts of intrinsic bootstrap current. At constant pressure, lowering of the electron density ne leads to a strong decrease in the collisionality with increasing electron temperature ν* ∼ T e − 3. Simultaneously, the conditions for low ne also benefit impurity accumulation. This paper reports on how radiative collapses due to central W accumulation were overcome by improved understanding of the changes to recycling and pumping, substantially expanded ECRH capacities for both heating and current drive, and a new solid W divertor capable of withstanding the power loads at low ne. Furthermore, it reports on various improvements to the reliability of the q-profile reconstruction. A candidate steady state scenario for ITER/DEMO (q95 = 5.3, βN.