Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring Mixture of Experts, In-context Learning and Data Augmentation for Building Robust QA

The task of learning from a limited number of examples (few-shot learning) is valuable because it uses only small amounts of data for prediction, making the models applicable in practical and realistic situations. In this work, we aim to train and fine-tune a robust QA model that can generalize well on out-of-domain datasets in few-shot settings. Our team explored mixture-of-experts (MoE), in-context learning, data augmentation, complemented by hyperparameter tuning to improve the domain adaptation robustness of DistilBERT-based[1] question answering systems. We significantly improved the baseline with a fine-tuned MoE model, while ending up with no metrics improvement with other approaches. The performance of in-context learning was subpar compared to the baseline, and data augmentation techniques were not able to generalize well in our experiments. Quantitatively, the final submission of our best approach, a fine-tuned MoE network without other techniques, achieved 43.876 EM and 61.933 F1 score and was ranked 4th out of 56 submissions in the test set.
Home-Country Productivity Spillovers from US Multinational Activity

This paper examines the role of multinationals in home-country productivity growth. A large body of work has examined the impact of multinational enterprises (MNEs) on domestic firms in foreign (host) countries through inward foreign direct investment (FDI). There is much less research on spillover effects from outward FDI on firms in the home countries of MNEs. However, policies promoting and subsidizing outward FDI have gained traction in developing countries as a means to potentially boost productivity growth. I evaluate this in the US context from 1989 to 2016 by estimating the impact of exposure to MNEs through horizontal and vertical linkages. Compared to existing work that relies on industry-level proxies of FDI and MNE exposure, I exploit firm-level variation in exposure to multinationals within the same product space and in buyer-supplier relationships. In addition, I distinguish between the endogenous network effect of exposure to a more productive firm, multinational or not, and the direct impact of being connected to an MNE. I find substantial direct positive effects of US multinationals on the productivity of their customers and competitors, and negative impacts on their suppliers.
Optimal Operation of Tri-Generation Microgrids Considering Demand Uncertainties

Tri-generation microgrids, also known as combined cooling, heat and power (CCHP) microgrids, have the potential to suffice the collective thermal and electrical demands of the microgrid residents. However, the energy demand of microgrids cannot be accurately predicted. Therefore, in this paper, robust optimization-based modeling for optimal operation of tri-generation microgrids is proposed. Uncertainty in cooling, heat, and power demands and worst-case realizations of uncertainties are considered. Initially, a deterministic problem is formulated which is then transformed into a min-max robust counterpart. Finally, a tractable robust counterpart is formulated by using the dual of the inner sub-problem. The formulated model is capable of providing feasible solutions for all possible realizations of uncertainties in energy demands (within the uncertainty bounds). The final tractable robust counterpart is simulated in CPLEX and various uncertainty cases are simulated. Simulation results have proved the robustness and effectiveness of the proposed optimization strategy.
Field monitoring of wheat seedling stage with hyperspectral imaging

Nutrient elements such as chlorophyll, nitrogen and water at the seedling stage are important key factors that could influence growth, development and even the final yield of wheat. In this study, the spectral data of canopy and single wheat plant leaves at seedling stage were acquired in field by using ASD non-imaging hyperspectrometer and imaging spectrometer respectively to establish prediction models for monitoring the growth at the seedling stage of wheat. According to the comparative analysis of models results built through partial least square algorithm (PLS), it was found that the models built using spectral data of canopy based on ASD non-imaging hyperspectrometer and imaging spectrometer both had low precision, which was possibly caused by background such as soil; while the model established from single wheat plant leaves based on the imaging spectrometer had a better effect. At last, the PLS model was established for chlorophyll SPAD value of wheat seedling leaves based on imaging spectrometry and its correlation coefficient R reached 0.8836, and the correlation coefficient R of the relevant model for nitrogen content was 0.8520, suggesting that the superiority of location monitoring of growth at seedling stage of wheat based on hyperspectral imaging is significant. Keywords: wheat seedling, monitoring, ASD, hyperspectral imaging, partial least squares DOI: 10.3965/j.ijabe. 20160905.1707 Citation: Wu Q, Wang C, Fang J J, Ji J W. Field monitoring of wheat seedling stage with hyperspectral imaging. Int J Agric & Biol Eng, 2016; 9(5): 143－148.
Discovery of a Novel Regulatory Mechanism of TNK1 by 14-3-3 and Its Ubiquitin Association Domain Provides a Potential Therapeutic Targeting Opportunity in Cancer

Discovery of a Novel Regulatory Mechanism of TNK1 by 14-3-3 and Its Ubiquitin Association Domain Provides a Potential Therapeutic Targeting Opportunity in Cancer Tsz Yin Chan Department of Chemistry and Biochemistry BYU Doctor of Philosophy While a relatively limited number of known oncogenes underlie a large percentage of cancers, a variety of new genes have emerged as low-frequency cancer drivers. Each of these new oncogenes represents a frontier for targeted therapy. However, the discovery of low-frequency targetable oncogenic drivers is challenging. This study focuses on the poorly understood Tyrosine kinase non-receptor-1 (TNK1), which has been reported to have both oncogenic and tumor suppressive functions. TNK1 has been identified to promote cancer cells survival and promote chemoresistance in multiple independent studies. On the other hand, whole-body constitutive deletion of TNK1 in mice caused an increase in spontaneous carcinomas and lymphomas. All in all, with no known regulatory mechanism and substrates of TNK1, the precise biological role of TNK1 is still unclear. To understand how TNK1 is regulated, we employed a proteomic approach to identify TNK1 interactors. We found out that TNK1 interacts with the phospho-binding protein 14-3-3 and this interaction is mediated by a cluster of MARK-mediated phosphorylations within the prolinerich domain. 14-3-3 binding retains TNK1 in the cytosol and maintains TNK1 in an inactive state. Release of TNK1 from 14-3-3 binding drives TNK1 to a heavy membrane fraction, where it becomes highly active. One unique feature of TNK1 is an ubiquitin association domain (UBA) on its C-terminus. Our data suggest that the UBA domain of TNK1 binds to poly-ubiquitin chains in nondiscriminatory manner. Remarkably, point mutations within the UBA that disrupt ubiquitin binding abolish TNK1 activation and oncogenic signaling, suggesting a unique UBA-centric mechanism of tyrosine kinase regulation. Finally, we used a structure-guided approach to identify a small molecule inhibiting TNK1 with high potency and selectivity. This compound, TP-5801, inhibits TNK1 dependent STAT3 phosphorylation. TP-5801 also prolongs the survival of mice injected via tail vein with TNK1-driven Ba/F3 cells and reduces tumor burden in a subcutaneous xenograft model. In conclusion, our data reveal a mechanism of TNK1 regulation that controls its oncogenic tyrosine kinase activity and a potential strategy for TNK1 inhibition.
DynaJET: Dynamic JVM Tuning for Spark

—Modern data analytics frameworks like Apache Spark are deployed at thousands of organizations regularly running diverse jobs that process petabytes of data. This has led to engineers carefully tuning conﬁgurations for these frameworks and even for speciﬁc jobs or queries. However, this is challenging as frameworks and their runtimes can have hundreds of knobs with many settings each, some with non-linear impacts on performance. Hence, tuning can require extensive analysis or end-to-end experimentation. This leaves end users with a choice of performing extra ofﬂine work, or performing experimentation on real workloads at the risk of signiﬁcant interim performance degradation. Weintroduce a dynamic tuning approach that we call Dy-naJET that offers several key beneﬁts over prior approaches. The foremost improvement in DynaJET is that it uses a dynamic tuning approach that accounts for the current system state at individual machines in the compute cluster rather than a static, load-oblivious conﬁguration. To do this, ﬁrst, it relies on a ﬁne-grained sampling scheme that captures throughput metrics for each job under different runtime conﬁguration parameters and machine states. Second, it uses these samples to continuously update tuning models, letting later instances of the same job make inferences about the performance of different conﬁgurations for the unique state of each machine in the compute cluster. We demonstrate DynaJET’s dynamic tuning atop the Spark compute engine using Java Virtual Machine (JVM) conﬁguration parameters as an example. With just three JVM parameters, we ﬁnd that a dynamic infrastructure can improve job completion time by up to 9.6% over a globally tuned JVM conﬁguration, and at least 3.3% on average.
Impact of next­generation sequencing defined human immunodeficiency virus pretreatment drug resistance on virological outcomes in the ANRS 12249 treatment­as­ prevention trial

Background. Previous studies in human immunodeficiency virus (HIV)-positive individuals on thymidine analogue backbone antiretroviral therapy (ART) with either nevirapine or efavirenz have suggested poorer virological outcomes in the presence of pretreatment drug resistance (PDR). We assessed the impact of PDR on virological suppression (VS; <50 copies/mL) in individuals prescribed primarily tenofovir/emtricitabine/efavirenz in rural KwaZulu-Natal within a treatment-as-prevention trial. Methods. Among 1557 HIV-positive individuals who reported no prior ART at study entry and provided plasma samples, 1328 individuals with entry viral load (VL) >1000 copies/mL had next-generation sequencing (NGS) of the HIV pol gene with MiSeq technology. Results were obtained for 1148 individuals, and the presence of PDR was assessed at 5% and 20% detection thresholds. Virological outcome was assessed using Cox regression in 837 of 920 ART initiators with at least 1 follow-up VL after ART initiation. Results. PDR prevalence was 9.5% (109/1148) and 12.8% (147/1148) at 20% and 5% thresholds, respectively. After a median of 1.36 years (interquartile range, 0.91–2.13), mostly on fixed-dose combination tenofovir/emtricitabine/efavirenz, presence of both nonnucleoside reverse transcriptase inhibitor (NNRTI)/nucleoside reverse transcriptase inhibitor PDR vs no PDR was associated with longer time to VS (adjusted hazard ratio [aHR], 0.32; 95% confidence interval [CI], 0.12–0.86), while there was no difference between those with only NNRTI PDR vs no PDR (aHR, 1.05; 95% CI, 0.82–1.34) at the 5% threshold. Similar differences were observed for mutations detected at the 20% threshold, although without statistical significance. Conclusions. NGS uncovered a high prevalence of PDR among participants enrolled in trial clinics in rural KwaZulu-Natal. Dual-class PDR to a mainly tenofovir/emtricitabine/efavirenz regimen was associated with poorer VS. However, there was no impact of NNRTI PDR alone. Trials . Clinical Trials DOH-27-0512-3974.
Molecular Characterization of Effective Biocontrol Agent against Aspergillus Flavus Causing Yellow Mold in Groundnut (Arachis HYPOGEA L.)

: Isolation of the rhizosphere microflora from the groundnut fields was done by serial dilution method and the microorganisms isolated were screened for antagonistic effect against Aspergillus flavus. Two fungal strains namely Penicilliumsp, and Trichodermaasperellum and four bacterial strains namely Pseudomonas fluorescence, Bacillus megaterium, Bacillus subtilis and Bacillus sp. were isolated and identified through morphological and biochemical characteristics from rhizosphere of groundnut. Trichodermaasperellum among fungal isolate and Pseudomonas fluorescence from bacterial isolate showed more antagonistic effect against Aspergillus flavus and thus proved to be potent biocontrol agents . Of the two potent biocontrol agents, Trichodermaasperellum showed maximum inhibitory zone against Aspergillus flavus and hence molecular characterization of isolate of Trichodermaasperellum was carried out. These studies revealed that revealed 99.84% similarity with ITS sequence of T. asperellum (Gen Bank Accession No. KY225658.1) when compared with GenBank Database using DDBJ BLAST search programme.
DIFFUSIVE PROCESSES MODELED ON THE SPECTRAL FRACTIONAL LAPLACIAN WITH DIRICHLET AND NEUMANN BOUNDARY CONDITIONS

In this paper we provide a comprehensive approach to the spectral fractional heat equation that combines purely analytic and probabilistic perspectives. Furthermore, we give two new results on the monotonicity properties of the spectral fractional heat diﬀusion with respect to the fractional parameter. The ﬁrst result deals with the spectral fractional heat kernel, evaluated at the initial singularity. The second result considers the probability for the corresponding stochastic process of being conﬁned in a subregion of the domain. In both results, the monotonicity property depends on the size of the ﬁrst non-zero eigenvalue. The cases of homogeneous Dirichlet and Neumann boundary conditions are addressed in details.
Principles of Human-Environment Systems (HES) Research

This paper presents the basic principles, applications, and a methodological discussion of the approach of Human-Environment Systems (HES). In general, HES includes all environmental and technological systems that are relevant for or affected by humans. The basic principles of the HES approach are: (1) human and environmental systems are constructed as complementary systems, (2) a hierarchy of human systems with related environmental systems are considered, (3) environmental systems are modeled in their immediate and delayed dynamic reactions to human action, (4) the behavior of the human system is modeled from a decision theoretic perspective differentiating between goal formation, strategy formation, strategy selection and action, (5) a conceptualization of different types of environmental awareness in each of these three steps can be developed, and finally (6) a distinction is made, with corresponding modeling reflecting this distinction, between primary and secondary feedback loops with respect to human action. We illustrate the principles with an example from bio-waste management. It is shown how the humanenvironment interaction can be analyzed.
Numerical and Experimental Study of The Air-Conditioning System of a Large Sports Hall

This research studies the internal environmental conditions in a large mechanically-conditioned sports hall experimentally and numerically. The Computational Fluid Dynamics (CFD) using the Engineering Software (ANSYS/FLUENT) conducts this analysis. The (Design Modeler) program designed the inner space of the hall, and the usual numerical findings of the program were compared and ratified with the experimental data gathered in a large sports hall at the Basra University Athletic Education College during the ten-day campaign. The metrics include the properties of the airflow at various internal space sites, as well as the surface temperature of the internal materials. In the model, various systems are applied to examine the ambient conditions occurring in the hall under various ventilation and professional conditions, which contribute to the various cooling trends. The numerical findings and the experimental tests include the amplitude of the airflow, temperature, relative humidity, and concentration of CO2 in the hall's door atmosphere when this hall is empty and when a sporting event is involved. There is a comparison of the numerical and experimental findings, and they indicate strong consensus.
BYU ScholarsArchive BYU ScholarsArchive Ultra-Low-Supply-Voltage Analog-to-Digital Converters Ultra-Low-Supply-Voltage Analog-to-Digital Converters

This thesis presents techniques to implement analog-to-digital converters (ADCs) under an ultra-low-supply-voltage of 0.2 V to reduce the power consumption. The thesis proposes a dynamic bulk biasing circuit to adjust the PMOS bulk voltage to balance the NMOS and PMOS drain currents to guarantee functionality in the presence of process, voltage, and temperature variations. The dynamic bulk bias circuit is analyzed rigorously to show its functionality. This thesis also describes a new comparator suitable for a 0.2-V supply using ac-coupling, stacked input pairs, and voltage-boosted load capacitor. A 10-bit 5-kS/s successive-approximation-register (SAR) ADC in a 180-nm CMOS process with a supply voltage of 0.2 V demonstrates these ideas. The ADC exhibits a differential nonlinearity (DNL) and integral nonlinearity (INL) within +0.42/-0.45 and +0.62/-0.67 LSB, respectively. The measured SFDR and SNDR at 5 kS/s with a Nyquist-frequency input are 65.9 dB and 52.1 dB, respectively. The entire ADC and dynamic bulk biasing circuitry consume 22 nW including leakage power to yield a figure-of-meirt (FoM) of 8.8 fJ/conv. -step. Measurements of multiple chips show the proposed dynamic bulk biasing fully recovers the ADC performance when the supply voltage is varied. The nW power consumption makes the design well suited for wireless sensor node and energy harvester applications.
Slide-Tone and Tilt-Tone: 1-DOF Haptic Techniques for Conveying Shape Characteristics of Graphs to Blind Users

We increasingly rely on up-to-date, data-driven graphs to understand our environments and make informed decisions. However, many of the methods blind and visually impaired users (BVI) rely on to access data-driven information do not convey important shape-characteristics of graphs, are not refreshable, or are prohibitively expensive. To address these limitations, we introduce two refreshable, 1-DOF audio-haptic interfaces based on haptic cues fundamental to object shape perception. Slide-tone uses finger position with sonification, and Tilt-tone uses fingerpad contact inclination with sonification to provide shape feedback to users. Through formative design workshops (n = 3) and controlled evaluations (n = 8), we found that BVI participants appreciated the additional shape information, versatility, and reinforced understanding these interfaces provide; and that task accuracy was comparable to using interactive tactile graphics or sonification alone. Our research offers insight into the benefits, limitations, and considerations for adopting these haptic cues into a data visualization context.
Opleiding Informatica Identifying anomalous trajectories from bird tracking data sets.

Trajectories of birds collected with GPS sensors can be compared with each other to ﬁnd trajectory patterns. There are a number of well-known algorithms available for ﬁnding similar trajectories that can be used to ﬁnd common ﬂy patterns of birds with their seasonal migration. However, uncommon ﬂy patterns can also be investigated to ﬁnd reasons why these ﬂy patterns are uncommon. To ﬁnd uncommon ﬂy patterns, we investigated similarity algorithms to detect anomalous trajectories and chose SSPD algorithm due to its capability to deﬁne a distance-based similarity on the whole structure of the two trajectories. This similarity algorithm will not only consider the route a bird took, but it will also look at the positions a bird has ﬂown. We have also chosen another algorithm, called t2vec , as it oﬀers calculation of the vector representation of trajectories. These vector representation consist of numbers that do not deﬁne a geo-spatial point, unlike GPS representation, and can then be used for clustering, such that potential diﬀerent clusters of birds can be made. A cluster of trajectories is a group of diﬀerent trajectories that all represent the same route a bird has ﬂown. The clusters from both SSPD and t2vec , as well as the computational time complexity of two approaches, were compared to identify which algorithm is the most eﬀective for anomalous trajectories. Our results indicated that t2vec should be preferred over SSPD because t2vec was able to obtain similar clusters when applied to a down-sampled dataset. The Euclidean distance for t2vec between the clusters of the down-sampled dataset and the complete dataset was much lower than the Euclidean distance for SSPD . Both the computational time and the run time was lower for t2vec compared to SSPD . Further research with t2vec was performed to investigate the underlying reason for anomalous trajectories by narrowing down to several possible causes (including the failures of the tracking devices, or behavior changes). Further research must be done to be able to conclude such hypotheses.
Software reliability allocation model of CNC system based on software architecture

In order to guarantee the implementation of reliability target, software reliability allocation model of CNC system was established based on software architecture. Software architecture of CNC system was set up, which decomposed CNC system into the functional units, reliability indexes of the system can be distributed into each component from top to bottom. The relative weight of software element in each level of the architecture was determined with analytic hierarchy process (AHP) method. The software reliability allocation model was built by taking the maximum practicability of CNC system as the target function, the reliability and cost function of component as the constraints. The reliability of each component was calculated through culture algorithm (CA). According to the result, the reliability allocation worked out is reasonable and feasible, and during the development of allocation model, the practicability of CNC system was guaranteed and development cost was also saved effectively.