Miracle-dz/UniFAR-FTUs huggingface dataset:
A Pedagogy of the Repressed? Critical Management Education and the Case Study

“On August 29, 2005, hurricane Katrina devastated the Gulf Coast of the United States precipitating a scene that could barely be believed: the complete evacuation and near-complete destruction of an entire American city. According to a 2006 evaluation report commissioned by The White House, the storm caused 1,330 deaths, resulted in about $96 billion in direct damage, destroyed or made unlivable 300,000 homes, forced the evacuation of 1.1 million people, and has created a huge pool of internally displaced people that have yet to return home (United States, 2006). It has also changed how the United States perceives itself in relation to the world with words entering the American vocabulary that had previously only been applied to developing countries: internally displaced people, refugee camps, foreign assistance” (Rostis & Helms Mills, 2009).
Evaluating Modern Data Centre Transport Protocols in OMNeT++/INET

In this paper we present our work towards an evaluation platform for data centre transport protocols. We developed a simulation model for NDP1, a modern data transport protocol in data centres, a FatTree network topology and per-packet ECMP load balancing. We also developed a data centre environment that can be used to evaluate and compare data transport protocols, such as NDP and TCP. We describe how we integrated our model with the INET Framework and present example simulations to showcase the workings of the developed framework. For that, we ran a comprehensive set of experiments and studied different components and parameters of the developed models.
BRAINSTEM ENCODING OF VOICE ONSET TIME: PRELIMINARY FINDINGS

Stop voicing contrasts are very common in the world’s languages and the perception of acoustic cues underlying these contrasts has been examined thoroughly with voice onset time (VOT) as the primary cue. While previous neurophysiological studies have revealed the cortical correlates of VOT, much less is known about how this critical voicing feature is encoded at the subcortical level. This study presents preliminary findings of auditory evoked potentials measuring activity from the brainstem of four neurotypical subjects to a VOT continuum (/ba//pa/). Spectrotemporal information corresponding to stop release and the onset of voicing was identified in the brainstem responses, and responses were compared across stimuli with respect to the duration between these two acoustic landmarks. Results show systematic changes in brainstem functions in response to the VOT alterations in the stimuli suggesting a high degree of neural synchrony to the timing of acoustic features at the brainstem level.
1 Characterizing Output Bottlenecks of a Production Supercomputer : Analysis and Implications

This paper studies the I/O write behaviors of the Titan supercomputer and its Lustre parallel file stores under production load. The results can inform the design, deployment and configuration of filesystems, and the design of I/O software in the application, operating system, and adaptive I/O libraries. We propose a statistical benchmarkingmethodology tomeasurewrite performance across I/O configurations, hardware settings and system conditions. Moreover, we introduce two relative measures to quantify the writeperformance behaviors of hardware components under production load. Besides designing experiments and benchmarking on Titan, we also verify the experimental results on one real application and one real application I/O kernel, XGC and HACC IO. These two are representative and widely used to address the typical I/O behaviors of HPC applications. In summary, we find that Titan’s I/O system is variable across the machine at fine time scales. This variability has two major implications. First, stragglers lessen the benefit of coupled I/O parallelism (striping). Peak median output bandwidths are obtained with parallel writes to many independent files, with no striping or write-sharing of files across clients (compute nodes). I/O parallelism is most effective when the application—or its I/O libraries—distributes the I/O load so that each target stores files for multiple clients and each client writes files on multiple targets, in a balanced way with minimal contention. Second, our results suggest that the potential benefit of dynamic adaptation is limited. In particular, it is not fruitful to attempt to identify “good locations” in the machine or in the file system: component performance is driven by transient load conditions, and past performance is not a useful predictor of future performance. For example, we do not observe diurnal load patterns that are predictable.
THE INTUITIVE RULE MORE A-MORE B: THE IMPACT OF A DYNAMIC GEOMETRY SOFTWARE

The aim of this study was twofold: First to examine the impact of the intuitive rule “more A-more B” on Cypriot students while dealing with geometric tasks and secondly to investigate whether teaching with the use of dynamic geometry may help children overcome the effects of the rule. The study was consisted of two parts. The first one was conducted with seventy-seven 6 graders who were presented with seven tasks concerning the sum of angles in triangles and quadrilaterals. The second was conducted with two 5 grade classes which were taught with two different teaching approaches, the traditional teaching approach and the approach with the use of a Dynamic Geometry software (DGs) called Euclidraw Jr. The results indicated that the intuitive rule has great impact on students’ reasoning and that the use of DGs was more effective than traditional teaching.
The Effect of Aerobic Training and Vitamin D Supplementation on Blood Pressure in Elderly Women with Nonalcoholic Fatty Liver and Vitamin D Deficiency

Background & Objective: The aim of this study was to investigate the effects of aerobic training (AT) and vitamin D (Vit D) supplementation on cardiovascular variables in elderly women with nonalcoholic fatty liver disease (NAFLD) and vitamin D deficiency. Materials & Methods: A total of forty women (60-65 years) with NAFLD (second or third grade) and vitamin D deficiency were recruited for the study. Participants were randomly assigned to four AT+Vit D, AT, Vit D, and control (C) groups and were allocated to receive either vitamin D ( ∼ 50000 IU • week for eight weeks) or placebo. The aerobic training protocol consisted of 40 -60 minutes of aerobic training at 60% - 75% of HRmax, 3 times a week for eight weeks. Anthropometric indices along with systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) were measured and mean of arterial pressure (MAP) was calculated. Results: AT+Vit D, Vit D and AT groups demonstrated a significant decrease in SBP, DBP, and HR, (P < 0.05) while, C group showed a significant increase in the mentioned variables (P < 0.05). Also after 8 weeks, AT + Vit D and AT groups showed significant decrease in the mean of MAP (P = 0.001; P = 0.018). Compared to the control group, significant differences in the SBP, DBP, and HR were observed in all groups. The mean SBP was significantly lower in AT+Vit D group comparing with AT, Vit D, and C groups. Also, no significant differences were observed between AT and Vit D groups in all variables. Conclusion: AT developed significant improvement in cardiovascular variables indicating SBP, DBP, MAP, and HR in elderly women with NAFLD and vitamin D deficiency. Meanwhile, AT combined with Vit D decreased SBP more significantly that might be incorporated in the management programs of the patients suffering from NAFLD in order to augment improvement in their blood pressure.
A Hierarchical Attention Network-Based Approach for Depression Detection from Transcribed Clinical Interviews

The high prevalence of depression in society has given rise to a need for new digital tools that can aid its early detection. Among other effects, depression impacts the use of language. Seeking to exploit this, this work focuses on the detection of depressed and non-depressed individuals through the analysis of linguistic information extracted from transcripts of clinical interviews with a virtual agent. Specifically, we investigated the advantages of employing hierarchical attention-based networks for this task. Using Global Vectors (GloVe) pretrained word embedding models to extract low-level representations of the words, we compared hierarchical local-global attention networks and hierarchical contextual attention networks. We performed our experiments on the Distress Analysis Interview Corpus Wizard of Oz (DAIC-WoZ) dataset, which contains audio, visual, and linguistic information acquired from participants during a clinical session. Our results using the DAIC-WoZ test set indicate that hierarchical contextual attention networks are the most suitable configuration to detect depression from transcripts. The configuration achieves an Unweighted Average Recall (UAR) of . 66 using the test set, surpassing our baseline, a Recurrent Neural Network that does not use attention.
Β-Sitosterol Ameliorates The Chemical Constituents Of Sunflower ( Helianthus Annuus L . ) Plants , Grown Under Saline Condition

The present experiment was carried out in fancied area at El-Mansoura University, Dakahlia Governorate during the growth period, from May to September (2013) to study the effect of different salinity levels (10, 20 and 30%sea water) and beta-sitosterol (10 -5 , 10 -7 and 10 -9 molar) on some chemical aspect of sunflower plants (Helianthus annus L.). The results indicated that salinity caused a reduction in chlorophyll a, b, a+b, a/b and Carotenoids as well as total pigments, carbohydrates contents with significant increasing sea water concentration during two stages of growth, 45 and 85 days from planting. Also a marked reduction in unsaturated fatty acids content accompanied with a marked increase in saturated fatty acids as compared to untreated control plants especially myristic acid. Increasing β-sitosterol concentration significantly increased chlorophyll a, b, a+b and Carotenoids as well as total pigments content of sunflower leave which reflected on carbohydrates fractions during both stages except chlorophyll a/b which had no significant effect during 45 and 85 days from the planting. Marked increases were observed in unsaturated fatty acid contents, as compared with the control plants. It can be noticed that the plants treated with β-sitosterol concentration with(10 -5 molar) attained the highest chlorophyll a, b, a+b, carotenoids and total pigments also, carbohydrates fractions as compared with the other treatments during both stages.
A Topic Modeling Framework for Humpback Whale Song

Humpback whales produce intricate hierarchical patterns of repeated vocal elements called songs. Studying these songs requires consistent classification of song components and measurement of variation over time and geographic location. Performing such classification and measurements manually is time consuming and can produce subjective results that differ from study to study, which makes it difficult to perform large scale analyses and impedes comparability between results of different analyses. For these reasons, efforts have been made to develop automated methods for performing such analyses. These analyses have operated at the level of song units, using a manual or automated detection pass as a precursor to modeling, and using the units isolated by the detection pass as the model’s input. This paper explores the application of a probabilistic topic modeling framework to modeling humpback whale song, which does not require a detection pass as a precursor, and is a mixed membership model, allowing the model to adapt the evolving nature of humpback whale song. The findings presented in this paper indicate that the framework is capable of differentiating song units and background noise, and to a certain extent, between song units themselves.
Genetic algorithm modification for production scheduling 301

Scheduling of production soundly affects its capacity especially if system does complex production jobs. In the theoretical part of the article an overview of the scheduling methods proposed in the literature was presented. In this paper it was stated a variant of job shop problem, in which jobs can overlap in some machines and omit others. Authors designed and presented here genetic algorithm to optimize solution of such a problem. The algorithm finds jobs sequence priority and in accordance with it schedules operations and calculates their completion time. An adequate problem was met in an examined plant, where 20 production jobs consisted of 11 to 20 operations assigned to at most 15 machines. Such big parameter numbers are crucial for big formal models and their solution algorithms. The designed algorithm proved to deal with parameters scale, as it found the schedule with 23,8% shorter jobs completion time in comparison with FIFO heuristic, that has been used so far by the plant.
The reviews of your manuscript submitted to Academy of Management Journal, Competitive tension: The awareness-motivation-capability perspective (#05-0027) are now complete. The reviewers and I all believe an integration of cognitive based competitor classification and competitive dynamics is an impo

R. Duane Ireland The reviews of your manuscript submitted to Academy of Management Journal, Competitive tension: The awareness-motivation-capability perspective (#05-0027) are now complete. The reviewers and I all believe an integration of cognitive based competitor classification and competitive dynamics is an important endeavor. Reviewer 2, for example, states when describing your paper: “it takes up the challenge of explaining competitive rivalry for the point of view of perceived inter-firm dynamics of competitioncertainly a worthwhile task in better understanding competitive moves. ” We also see merit in the application of the awareness-motivation-capability (AMC) perspective. For example, Reviewer 1 comments: “there have been many prior research efforts that have leveraged the awareness-motivationcapability perspective without really addressing the critical issues of how, exactly, these play out in decision makers’ minds. ” Finally, we are impressed by your survey methodology to answer your research questions. Texas A&M University AMJ@mays.tamu. edu
On the Use of Pitch Features for Disordered Speech Recognition

Pitch features have long been known to be useful for recognition of normal speech. However, for disordered speech, the significant degradation of voice quality renders the prosodic features, such as pitch, not always useful, particularly when the underlying conditions, for example, damages to the cerebellum, introduce a large effect on prosody control. Hence, both acoustic and prosodic information can be distorted. To the best of our knowledge, there has been very limited research on using pitch features for disordered speech recognition. In this paper, a comparative study of multiple approaches designed to incorporate pitch features is conducted to improve the performance of two disordered speech recognition tasks: English UASpeech, and Cantonese CUDYS. A novel gated neural network (GNN) based approach is used to improve acoustic and pitch feature integration over a conventional concatenation between the two. Bayesian estimation of GNNs is also investigated to further improve their robustness.
A Silicon Germanium CMOS Linear Voltage Regulator for Wireless Agricultural Applications

This thesis presents the design, simulation and test results of a silicon germanium (SiGe) complementary metal-oxide-semiconductor (CMOS) linear regulator. The objective of the circuit is to power other analog devices regardless of the load current and input voltage changes. The application of this regulator is to be part of a project developing a miniaturized semiconductor platform that can be inserted into stems of crops in order to measure data inside the plant and then send it wirelessly to the user. The linear regulator was designed on a BiCMOS SiGe 0. 13μm which is a GlobalFoundries process. It has been tested at room temperature and at 85 oC with a supply voltage of 2.5 V and it holds an output of 1.2 V. The device demonstrates line regulation of 5 % % and load regulation of 0.19 % as well as rejection of the power supply satisfying the specifications proposed. ©2019 by Aminta Naidili Castillo Robles All Rights Reserved Acknowledgements I would like to thank Dr. Alan Mantooth for the opportunity of being part of his IC design team. I am grateful for receiving me and trusting me with the tasks that I was assigned. I thank my committee members – Dr. Simon Ang, and Dr. Jia Di for supporting my work. My sincerest gratitude goes the administrative staff. These ladies work behind curtains, and they take a lot of stress from our shoulders. The technical support team was also always there to solve any issues that came up. I would like to thank my teammates, who answered my questions and helped me out when in doubt. The help given by Maria Raquel Benavides Herrera goes beyond been a coworker, without her support and encouragement I would not have made it this far. Lastly, I thank the University of Arkansas and the city of Fayetteville for opening its doors and receiving me. This place was my home away from home and I will be forever thankful for accepting me here. Dedication I would like to dedicate this thesis to my parents, Aminta del Carmen Robles Cordoba and Dionel Celiano Castillo Tristan. Thank you for your love and for being the fuel that keeps me going. Thank you for helping me fly. I would also like to dedicate my thesis to the memory of Dr. Etilvia Maria Arjona Chang who believed in me even when I did not. Your passion, tenacity, and kindness will always be my inspiration.
KU-ARTLEX : A SINGLE-SPEAKER EMA DATABASE FOR MODELING THE ARTICULATORY STRUCTURE OF THE LEXICON

Articulatory data (6-channel electro-magnetic articulography, EMA) was recorded on a 26,793-word database of English words – replicating the set used in the Massive Auditory Lexical Decision project [15] – along with two repetitions of 1,200 controlled CVC syllables based on the California Syllable Test [16], from a single male native speaker of Midwestern American English. The primary aim of this database is to serve as a window on the articulatory structure of the lexicon; i.e., what gestural profiles distinguish words in English, and what constitutes minimality (how are minimal pairs defined, if at all) from an articulatory standpoint? Further, using this open-access database, comparable perception experiments testing the predictability of word recognition patterns from articulatory and acoustic profiles can now be run by multiple research groups, providing greater clarity to broader theoretical debates on the nature of the encoding of the speech signal.
Optimizing Voice Activity Detection for Noisy Conditions

In this work, we focus our attention on how to improve Voice Activity Detection (VAD) in noisy conditions. We propose a Convolutional Neural Network (CNN) based model, as well as a Denoising Autoencoder (DAE), and experiment against acoustic features and their delta features in noise levels ranging from SNR 35 dB to 0 dB. The experiments compare and find the best model configuration for robust performance in noisy conditions. We observe that combining more expressive audio features with the use of DAEs improve accuracy, especially as noise increases. At 0 dB, the proposed model trained with the best feature set could achieve a lab test accuracy of 93.2% (averaged across all noise levels) and 88.6% inference accuracy on device.We also compress the neural network and deploy the inference model that is optimized for the app so that the average on-device CPU usage is reduced to 14% from 37%.
Towards the enrichment of terminological resources by scientific corpora analysis

The research presented in this paper explores the possibility of enriching terminological databases through the analysis of recent scientific publications. Our main concern is to evaluate how useful automatic term extraction can be to a human expert. To carry out our experiment, we constructed two corpora of recent scientific papers in two different sub-domains of the bio-medical sciences. Then we proceeded with three steps: automatic term extraction and ranking from a set of corpora of scientific papers; evaluation of the overlap of the candidate terms (CTs) extracted from the corpora and those present in the multidisciplinary terminology portal TermSciences; and evaluation by domain experts of the three sets of the top 200 CTs extracted from the different corpora. To extract terms we used the Sensunique Platform, a web based platform for building terminological resources. Our results show that only about 10% of the extracted CTs are present in the TermSciences resource, which means that many of the extracted CTs, if validated, could potentially be used to enrich the terminological database. Furthermore, the expert evaluation of the top 200 terms for each sub-corpus shows clearly that about 75% of these CTs are correct terms in the respective domains. This validates our ranking algorithm.
Review of Channel Estimation for Candidate Waveforms of Next Generation Networks

The advancement in wireless communication applications encourages the use of effective and efficient channel estimation (CE) techniques because of the varying behaviour of the Rayleigh fading channel. In most cases, the emphasis of most proposed CE schemes is to improve the CE performance and complexity for ensuring quality signal reception and improved system throughput. Candidate waveforms whose designs are based on filter bank multi-carrier (FBMC) modulation techniques such as filter bank orthogonal frequency division multiplexing based on offset quadrature amplitude modulation (OFDM-OQAM), universal filtered multicarrier (UFMC) and generalised frequency division multiplexing based on offset quadrature amplitude modulation (GFDM-OQAM) are no exception to the use of these proposed CE techniques in the literature. These schemes are considered as potential waveform candidates for the physical/media access control layer of the emerging fifth generation (5G) networks. Therefore, pinpoint CE techniques represent an important requirement for these waveforms to attain their full potentials. In this regard, this paper reviews the concept of CE as applicable to these waveforms as well as other waveform candidates under consideration in the emerging 5G networks. Since the design of the majority of the waveform candidates is filter based, a review of the general filter design considerations is presented in this paper. Secondly, we review general CE techniques for candidate waveforms of next generation networks and classify some of the studied CE techniques. In particular, we classify the CE schemes used in filter bank OFDM-OQAM and GFDM-OQAM based transceivers and present a performance comparison of some of these CE schemes. Besides, the paper reviews the performances of two linear CE schemes and three adaptive based CE schemes for two FBMC based waveform candidates assuming near perfect reconstruction (NPR) and non-perfect reconstruction (Non-PR) filter designs over slow and fast frequency selective Rayleigh fading channels. The results obtained are documented through computer simulations, where the performances of the studied CE schemes in terms of the normalised mean square error (NMSE) are analysed. Lastly, we summarise the findings of this work and suggest possible research directions in order to improve the potentials of the studied candidate waveforms over Rayleigh fading channels.