Miracle-dz/UniFAR-FTUs huggingface dataset:
Embedding of Functional Human Brain Networks on a Sphere

Human brain activity is often measured using the blood-oxygen-level dependent (BOLD) signals obtained through functional magnetic resonance imaging (fMRI). The strength of connectivity between brain regions is then measured as a Pearson correlation matrix. As the number of brain regions increases, the dimension of matrix increases. It becomes extremely cumbersome to even visualize and quantify such weighted complete networks. To remedy the problem, we propose to embed brain networks onto a sphere, which is a Riemannian manifold with constant positive curvature. The Matlab code for the spherical embedding is given in https://github.com/laplcebeltrami/sphericalMDS.
Neural Question Answering on SQuAD 2.0

This work aims to investigate innovative designs of model architectures that can help boost performance on the SQuAD 2.0 dataset, without using pre-trained language models. Since around half of the questions are unanswerable, it is important for the model to tactfully abstain from answering. The main contribution is a self-implemented QANet architecture with extensions on the embedding layer and the output layer. By using unified encoding for the context and question before feeding into context-query attention and employing threshold-based answer verification during testing, the model achieves stronger out-of-sample performance than the original QANet baseline. With a novel debiased ensemble method, the model achieves an EM score of 67.68 and F1 score of 70.53 on the test leaderboard for the IID SQuAD track.
Arima Model for Forecasting of Monthly Rainfall and Temperature in the Lake Victoria Basin

The rise in global temperature which is global warming has lead to erratic and disruptive weather pattern in several regions of the world including the area surrounding the Lake Victoria basin. Likewise, economic activities associated with Lake Victoria and its Basin such as agriculture, (cid:12)shing, mining and transportation are signi(cid:12)cantly a(cid:11)ected by this climatic changes. The primary cause of negative impact that stems from this changes is lack of reliable information that can be used to predict and address the climatic variations within the basin. The objective of this research is to identify a suitable time series model that can be used to analyse and predict this weather variations and pattern around the Lake Victoria basin. This research uses Box jenskin methodology to build ARIMA(2,0,1) model for rainfall pattern around Lake Victoria basin. The data is obtained from three Kenya Meteorological Department weather stations as secondary data from the years 2008 to 2014. In this research, data from the years 2008 to 2010 was used to estimate the values for the years 2011 to 2013. The relationship from the research showed a strong positive relationship which indicates high level of accuracy on predictability by the model.
Effects of Two Commercial Protein Diets on the Health of Two Imago Ages of Apis mellifera L. Reared in Laboratory

Simple Summary Beekeepers often feed their bees with supplemented artificial diets. The formulation of an integrative diet for honey bee colonies able to prevent nutritional deficiencies is yet to be found. In this work, the effects of pollen diet substitution with commercial protein diets in newly emerged bees (that still feed a little on pollen) and in forager bees (that usually do not feed on pollen) were tested. Results obtained suggest that commercial protein diets do not compensate pollen diets in newly emerged bees and do not determine an increase in life span or immunity in forager bees. Further investigations on the effect of concentration and quality of proteins are desirable in order to provide beekeepers with scientific evidence on protein-based feeding. Abstract Protein-supplemented artificial diets are widely used by beekeepers during winter and whenever food availability is low, yet no data are available concerning their effects on bees’ health. In this work, the effects of two commercial diets enriched with 1.7% and 7.7% protein concentration on feed intake, survival rate, glucose oxidase, phenoloxidase and glutathione S-transferase in newly emerged and forager bees were tested. Administration of a 7.7% protein-enriched diet significantly reduced the lifespan of both newly emerged and forager bees, while only in foragers a significantly higher feed intake was recorded. In newly emerged bees, administration of a high-protein-enriched diet stimulated glucose oxidase production at the 10th day of feeding, determined a reduction of phenoloxidase and did not affect glutathione S-transferase activity. In forager bees, a high level of protein inclusion did not determine any significant variation in either glucose oxidase, phenoloxidase or glutathione S-transferase activity. Therefore, the results obtained in this investigation suggest that administration of commercial protein diets negatively affect honey bee health, determining an increase in mortality. Further investigations on the effect of concentration and quality of proteins are desirable to provide beekeepers with scientific evidence on protein feeding.
The TAC Toolkit: Supporting Design for User Acceptance of Health Technologies from a Macro-Temporal Perspective

User acceptance is key for the successful uptake and use of health technologies, but also impacted by numerous factors not always easily accessible nor operationalised by designers in practice. This work seeks to facilitate the application of acceptance theory in design practice through the Technology Acceptance (TAC) toolkit: a novel theory-based design tool and method comprising 16 cards, 3 personas, 3 scenarios, a virtual think-space, and a website, which we evaluated through workshops conducted with 21 designers of health technologies. Findings showed that the toolkit revised and extended designers’ knowledge of technology acceptance, fostered their appreciation, empathy and ethical values while designing for acceptance, and contributed towards shaping their future design practice. We discuss implications for considering user acceptance a dynamic, multi-stage process in design practice, and better supporting designers in imagining distant acceptance challenges. Finally, we examine the generative value of the TAC toolkit and its possible future evolution.
Investigation of transport of glibenclamide drug across micro-pore supported model membrane using electro analytical methods

Glibenclamide is a second generation sulfonyl urea compound used as an oral hypoglycemic or anti diabetic agent, a class of drug used to treat type-2 diabetes mellitus. The bilayer lipid membrane systems have been employed extensively as an experimental model of bio membranes. It is of major importance in medical research, particularly in the study of mechanism of a number of life saving therapeutic agents where a lipid bilayer is the primary site of interaction. The objective of this study was to investigate the transport of glibenclamide across micro-pore supported model bilayer lipid membrane. In this study, lipid bilayer membrane was prepared from L-alpha - phosphotidylcholine. Conductometric and potentiometric techniques were used to measure membrane conductance and membrane potential respectively as a function of concentration of the glibenclamide solution and temperature of the electrochemical cell maintained. The observed data were used to evaluate selectivity and activation parameters by making use of mathematical expressions derived on the basis of non-equilibrium and transition state theories. From membrane potential study, thermodynamically effective fixed charge density (ØX) and transport number of anions (t - ) obtained were 42.6 meq/lit and 0.76 respectively and membrane conductance of 0.1 molar glibenclamide drug solution at 37°C showed 26.11 + 0.01 (µs/cm), at this concentration and temperature values of activation parameters (Ea, ΔG*, Δ H*, -ΔS*) obtained were: 2516.47J/mole, 61605.71 J/mole,38.90J/mole and 206.60 J/k mole respectively. The observed and evaluated data indicated that selective membrane behavior was more pronounced in the dilute range and the drug molecules were diffused across the membrane passively. Hence it might be concluded that small amount of drug is more effective in getting the desired effect.
A review on measurement science needs for real-time control of additive manufacturing metal powder bed fusion processes

Additive manufacturing technologies are increasingly used in the development of new products. However, variations in part quality in terms of material properties, dimensional tolerances, surface roughness and defects limit its broader acceptance. Process control today based on heuristics and experimental data yields limited improvement in part quality. In an effort to identify the needed measurement science for real-time closed-loop control of additive manufacturing (AM) processes, this paper presents a literature review on the current AM control schemes, process measurements and modelling and simulation methods as it applies to the powder bed fusion process, though results from other processes are reviewed where applicable. We present our research findings to identify the correlations between process parameters, process signatures and product quality. We also present research recommendations on the key control issues to serve as a technical basis for standards development in this area. Complimentary details to this paper with summary tables, range of values, preliminary correlations and correlation figures can be accessed from a National Institute of Standards and Technology Report (http://nvlpubs.nist.gov/nistpubs/ir/2015/NIST.IR.8036.pdf). This paper is developed based on the report.
Evaluating Natural Language Models on Technical Query Tagging

In this study, the relative performances of a non-parametric supervised learning method; a non-recurrent, dense neural architecture; a sequential neural model; and a Bidirectional Encoder Representations from Transformers (BERT) model were evaluated on the task of identifying the broader subject of a technical question. This comparison was done to investigate whether the task of identifying the suitable tags for a technical computer science question, and the general task of identifying the topic(s) of a technical piece of text, is one that is aided by temporal and sequential inference and the ability to derive context from the underlying patterns and structures of sentences. This study involved using the titles, bodies, and tags of 300 thousand Stack Overflow questions to train, fine-tune, and test the aforementioned models. The multi-layer bidirectional LSTM model generated the lowest performance metrics. Meanwhile, the best performance was achieved by the BERT model, with a recall of over 90% and F-1 score around 0.45 in both the validation and held-out test sets.
This paper is included in the Proceedings of the 19th USENIX Symposium on Networked Systems Design and Implementation. C2DN: How to Harness Erasure Codes at the Edge for Efficient Content Delivery

Content Delivery Networks (CDNs) deliver much of the world’s web and video content to users from thousands of clusters deployed at the “edges” of the Internet. Maintain-ing consistent performance in this large distributed system is challenging. Through analysis of month-long logs from over 2000 clusters of a large CDN, we study the patterns of server unavailability. For a CDN with no redundancy, each server unavailability causes a sudden loss in performance as the objects previously cached on that server are not accessible, which leads to a miss ratio spike. The state-of-the-art mitigation technique used by large CDNs is to replicate objects across multiple servers within a cluster. We ﬁnd that although replication reduces miss ratio spikes, spikes remain a performance challenge. We present C2DN, the ﬁrst CDN design that achieves a lower miss ratio, higher availability, higher resource efﬁciency, and close-to-perfect write load balancing. The core of our design is to introduce erasure coding into the CDN architecture and use the parity chunks to re-balance the write load across servers. We implement C2DN on top of open-source production software and demonstrate that compared to replication-based CDNs, C2DN obtains 11% lower byte miss ratio, eliminates unavailability-induced miss ratio spikes, and reduces write load imbalance by 99%.
Forage production and nutritional composition of four varieties of Avena sativa L. in Ubaté, Cundinamarca, Colombia

Objective : To evaluate the forage performance and chemical composition of four varieties of Avena sativa Materials and Methods : The essay was conducted in the Agro-Environmental Unit El Tíbar, of the University of Cundinamarca, located on the Palo Gordo district, Colombia. The experiment was conducted through a randomized block design. Each block corresponded to two periods of planting moments (October-November and April-May). The treatments corresponded to four A. sativa varieties: cayuse, konan, everleaf and suprema. The experimental units had plots of 4 m 2 . Plant height was measured and cutting was done with a frame of 1 x 1 m to determine forage production. Samples were taken to measure quality by a chemical-nutritional analysis. Results : The average value of plant height at the moment of cutting was 167 cm, with significant differences (p < 0,05) among varieties. The variety cayuse stood out, with 175 cm, which was the tallest. No significant differences were shown regarding the biomass production, whose average was 31,5 ± 7,26 t/ha. With regards to the chemical composition, dry matter showed significant differences (p < 0,05), with the highest values for the variety everleaf in both planting seasons, with an average of 24,6 %. Crude energy reached an average of 4 208 kcal/kg, with the highest values (p < 0,05) in the variety suprema. The dry matter digestibility at 48 h averaged 54,87 %, without significant differences among the four A. sativa varieties. The same occurred for the degraded protein in the rumen (average of 94,5 %) and degradability of the neutral detergent fiber (53,8 %). Conclusions : The planting season did not influence biomass production or the nutritional composition of the different evaluated oat varieties, which obtained similar results.
BYU ScholarsArchive BYU ScholarsArchive EMS Mutagenesis in Quinoa: Developing a Genetic Resource EMS Mutagenesis in Quinoa: Developing a Genetic Resource

Chenopodium quinoa , a South American pseudocereal, has valuable agricultural traits such as salt tolerance and drought tolerance, and it has beneficial nutritional properties such as high protein content and a complete amino acid profile. However, problems including disease susceptibility, low harvest index, lodging, seed shattering, low heat tolerance, and saponin content plague quinoa. Genetic resources for quinoa are needed to fix these problems and make quinoa more available throughout the world. We used ethyl methanesulfonate (EMS) to create a mutant population of QQ74 quinoa (USDA GRIN PI 614886) of 5,030 mutant families. We did whole exome sequencing (WES) on 44 mutant families. Using the recently published quinoa reference genome and MAPS, a mutation detection pipeline, we found a mutation rate of 11.35 mutations/Mb in these families. We also used whole genome sequencing (WGS) to calculate a mutation rate of 21.67 mutations/Mb in an additional nine mutant families. To demonstrate the utility of this population as a genetic resource, we found an EMS-induced nonsense mutation in the betalain synthesis pathway that prevents red betacyanins from accumulating in the hypocotyl of quinoa. With the mutation rates in our population, we calculate that analysis of 300 mutant families will yield 3-7 mutations in any gene of interest, which will facilitate forward and reverse genetic studies in quinoa.
Characterization and Modeling of TSV Based 3-D Integrated Circuits

Through silicon via (TSV) based three-dimensional integrated circuits have rapidly progressed over the past decade. TSV based three-dimensional integration has the potential to significantly boost the performance and capabilities of state-of-art integrated circuits, while supporting the integration of disparate heterogeneous technologies. The research presented here provides insight into some of the most pressing issues currently being addressed by the research community, and provides guidelines for designing these evolving heterogeneous 3-D systems. The organization of the dissertation begins with an introduction to TSV electrical models, power delivery, and thermal behavior in 3-D ICs. Characterization and physical design methodologies for 3-D integrated circuits are discussed. Electrical modeling of TSVs is presented, culminating in the development of closed-form expressions for the TSV resistance, capacitance, and inductance. Synchronization and power delivery are critical design considerations in 3-D ICs. Models of three distinct clock distribution networks are provided, and a comparison of the power and delay of each topology is presented. Three power delivery topologies are discussed, with experimental evidence describing the effects of the TSV density on the noise profile
PCA and LDA for EMG-based control of bionic mechanical hand

Electromyography (EMG) has some good abilities for bionic mechanical hand's control and researchers have proposed many kinds of methods for EMG classification. Principal Components Analysis (PCA) which is an ideal tool for dimension reduction tool was introduced for EMG classification. Linear Discriminant Analysis (LDA) performs outstandingly on classification. This paper does a comparative study on PCA and LDA for EMG classification, mainly including LDA for raw EMG, LDA for features, PCA and LDA for raw EMG and PCA and LDA for features. Here five time-domain features and four frequency-domain features are selected. The five hand motions including hand closing, hand opening, index finger pinching, middle finger pinching and hand relaxing are selected for classification. The result shows PCA and LDA for features obtain 99.0% motion success rate and 99.8% success rate of classification. The bionic mechanical hand got a good performance. c 2012 IEEE.
Five studies evaluating the impact on mental health and mood of recalling, reading, and discussing fiction

Does reading fiction improve mental health and well-being? We present the results of five studies that evaluated the impact of five forms of exposure to fiction. These included the effects of recalling reading fiction, of being prescribed fiction, of discussing fiction relative to non-fiction, and of discussing literary fiction relative to best-seller fiction. The first three studies directly recruited participants; the final two relied on scraped social media data from Reddit and Twitter. Results show that fiction can have a positive impact on measures of mood and emotion, but that a process of mnemonic or cognitive consolidation is required first: exposure to fiction does not, on its own, have an immediate impact on well-being.
Utilizing computer vision for facial behavior analysis in schizophrenia studies: A systematic review

Background Schizophrenia is a severe psychiatric disorder that causes significant social and functional impairment. Currently, the diagnosis of schizophrenia is based on information gleaned from the patient’s self-report, what the clinician observes directly, and what the clinician gathers from collateral informants, but these elements are prone to subjectivity. Utilizing computer vision to measure facial expressions is a promising approach to adding more objectivity in the evaluation and diagnosis of schizophrenia. Method We conducted a systematic review using PubMed and Google Scholar. Relevant publications published before (including) December 2021 were identified and evaluated for inclusion. The objective was to conduct a systematic review of computer vision for facial behavior analysis in schizophrenia studies, the clinical findings, and the corresponding data processing and machine learning methods. Results Seventeen studies published between 2007 to 2021 were included, with an increasing trend in the number of publications over time. Only 14 articles used interviews to collect data, of which different combinations of passive to evoked, unstructured to structured interviews were used. Various types of hardware were adopted and different types of visual data were collected. Commercial, open-access, and in-house developed models were used to recognize facial behaviors, where frame-level and subject-level features were extracted. Statistical tests and evaluation metrics varied across studies. The number of subjects ranged from 2-120, with an average of 38. Overall, facial behaviors appear to have a role in estimating diagnosis of schizophrenia and psychotic symptoms. When studies were evaluated with a quality assessment checklist, most had a low reporting quality. Conclusion Despite the rapid development of computer vision techniques, there are relatively few studies that have applied this technology to schizophrenia research. There was considerable variation in the clinical paradigm and analytic techniques used. Further research is needed to identify and develop standardized practices, which will help to promote further advances in the field.
A Reconfigurable Directional Coupler Using a Variable Impedance Mismatch Reflector for High Isolation

This letter proposes a reconfigurable directional coupler that uses a variable impedance mismatch reflector to achieve high isolation characteristics in the antenna front end. The reconfigurable coupler consists of a directional coupler and a single-pole four-throw (SP4T) switch with different load impedances as a variable load mismatch reflector. Selection of the load impedance by the reflector allows cancellation of the reflected signal due to antenna load mismatch and the leakage from the input to isolation port of the directional coupler, resulting in high isolation characteristics. The performance of the proposed architecture in separating the received (Rx) signal from the transmitted (Tx) signal in the antenna front end was verified by implementing and testing the reconfigurable coupler at 917 MHz for UHF radio-frequency identification (RFID) applications. The proposed reconfigurable directional coupler showed an improvement in the isolation characteristics of more than 20 dB at the operation frequency band.