Miracle-dz/UniFAR-FTUs huggingface dataset:
A Comparison Study of Saliency Models for Fixation Prediction on Infants and Adults

Various saliency models have been developed over the years. The performance of saliency models is typically evaluated based on databases of experimentally recorded adult eye fixations. Although studies on infant gaze patterns have attracted much attention recently, saliency-based models have not been widely applied for prediction of infant gaze patterns. In this paper, we conduct a comprehensive comparison study of eight state-of-the-art saliency models on predictions of experimentally captured fixations from infants and adults. Seven evaluation metrics are used to evaluate and compare the performance of saliency models. The results demonstrate a consistent performance of saliency models predicting adult fixations over infant fixations in terms of overlap, center fitting, intersection, information loss of approximation, and spatial distance between the distributions of saliency map and fixation map. In saliency and baselines models performance ranking, the results show that graph-based visual saliency model and Itti model are among the top three contenders, infants and adults have bias toward the centers of images, and all models and the center baseline model outperformed the chance baseline model.
Capacity-Aware and Delay-Guaranteed Resilient Controller Placement for Software-Defined WANs

Currently, one of the main enablers for network evolution is software-defined networking (SDN), where the control plane is decoupled from the data plane. A controller, as a (logically) centralized entity in the control plane, is the Achilles’ heel of SDN resilience since its failure would affect the proper functioning of the entire network. The resilience of the control plane is strongly linked to the controller placement problem, which deals with the positioning and assignment of controllers to the forwarding devices (i.e., switches). A resilient controller placement problem needs to assign more than one controller to a switch while it satisfies certain quality of service requirements. In this paper, we propose a solution for such a problem that, unlike most of the former studies, takes both the switch-controller /inter-controller latency requirements and the capacity of the controllers into account to meet the traffic load of switches. The proposed algorithms, one of which has a polynomial-time complexity, adopt a clique-based approach in graph theory to find high-quality solutions heuristically. It is evaluated with real wide area network (WAN) topologies and the corresponding results are extensively analyzed. The resultant studies equip the service providers with helpful insights into the design of a resilient software-defined WAN.
Facial Expression Classification using Deep Extreme Inception Networks

Facial expression classification p lays c rucial role in human-computer interaction. A large number of automated methods have been proposed since the past decades. Recently, deep learning is broadly applied in computer vision field as well as facial expression classification. The reasons are to avoid complex feature extraction process and obtained satisfied classification p erformance. In this work, w e p ropose a deep convolutional neural networks (CNNs) model, inspired from XCEPTION, to classify seven groups of facial expressions. To efficiently use o f m odel parameters, the model a rchitecture has only 2.2 million parameters which is about 10 times less than XCEPTION. The experimental results on FER-2013 dataset show that our model offers comparable accuracy (0.7169) to the state-of-the-art methods and the upper-bound level of human accuracy $( 0.65 \pm 5)$. In addition, our model uses less number of parameters than the state-of-the-art models and without using extra features and data augmentation.
Carcass characteristics and meat quality of purebred Pakchong 5 and crossbred pigs sired by Pakchong 5 or Duroc boar

Objective This study investigated carcass characteristics and meat quality of purebred Pakchong 5, crossbred pigs sired by Pakchong 5, and crossbred pigs sired by Duroc. Methods Forty-eight pigs (average body weight of 22.25 kg) were composed of three groups as purebred Pakchong 5 (PP), Large White×Landrace pigs sired by Pakchong 5 (LWLRP), and Large White×Landrace pigs sired by Duroc (LWLRD). Each group consisted of eight gilts and eight barrows. At 109-day-raising period, pigs were slaughtered, and carcass characteristics were evaluated. Longissimus thoracis (LT) muscles from left side of carcasses were evaluated for meat quality and chemical composition. Data were analyzed using general linear model procedure, where group, sex, and their interaction were included in the model. Results The PP had greater carcass, total lean, and ham percentages than crossbred pigs (p< 0.05). LWLRP had thicker backfat and more carcass fat percentage than LWLRD (p<0.05). There were no differences (p>0.05) on cutting percentages from tender loin, loin, boston butt, and picnic shoulder among groups. The PP and LWLRP had larger loin eye area (LEA) than LWLRD (p<0.05). Gilts had more loin percentage and lower L* value than barrows (p<0.05). No meat color parameters (L*, a*, and b*) were affected by groups (p>0.05). PP and LWLRP had larger muscle fiber diameters than LWLRD (p<0.05). However, water holding capacity, Warner-Bratzler shear force values, and chemical composition of LT were not affected by group or sex (p>0.05). Conclusion Pakchong 5 purebred has good carcass and lean percentages. Compared to Duroc crossbred pigs, Pakchong 5 crossbreds have similar carcass and lean percentages, larger LEA, and slightly more carcass fat, with comparable meat quality and chemical composition. Pakchong 5 boars are more affordable for very small- to medium-scale pig producers.
Robust Multigroup Multicast Transmission for Frame-Based Multi-Beam Satellite Systems

We investigate robust multigroup multicast transmission for frame-based multi-beam satellite communication systems with full frequency reuse. To mitigate the effect of outdated channel state information (CSI), we first investigate robust multigroup multicast precoding that maximizes the minimum average signal to interference plus noise ratio (SINR) under the per-beam power constraints. We show the relationship between the robust max–min fair problem and the robust power minimization problem with partial CSI and propose a low complexity precoder for the robust power minimization problem. We then investigate user clustering which only requires partial CSI. We show that the approximated average SINR can be maximized provided that the estimated channel vectors of the users in the same cluster are linearly dependent while those in different clusters are mutually orthogonal. Motivated by this user clustering condition, we further propose a low-complexity user clustering algorithm. Simulation results demonstrate that the proposed robust approach can provide substantial performance gains over the conventional approach in multi-beam satellite communication systems.
LegUp-NoC: High-Level Synthesis of Loops with Indirect Addressing

Loops with indirect addressing, of the type A[B[i]], are notoriously difficult to parallelize using contemporary FPGA High-Level Synthesis (HLS) tools. In contrast, loops with direct addressing can be parallelized using compile-time approaches by replicating datapaths and memory blocks. Such compile-time approaches do not work for indirect addressing as indices B[i] are not known until runtime. Consequently, since addresses may point to any memory bank, HLS tools generate expensive crossbars between datapaths and memory banks. As all datapaths may target the same bank in a given cycle, a sequential arbitration is provided to control the crossbar multiplexers. In this paper, we show how to overcome the resource and performance limitations of existing tools using a Network-on-Chip (NoC) approach to route indirect indices to the memory banks over a packet-switched fabric. NoCs provide scalable connectivity between FPGA datapaths and memory banks and allow parallel routing of packets from datapaths to the banks. We develop a LegUp 5.0 compiler pass that (1) handles loops with indirect memory access by inserting NoCs into the circuit as required, (2) provides a performance and resource tuning framework for optimizing the resulting hardware, and (3) obviates the need for NoC expertise during programming. We quantify the effectiveness of our approach across a range of kernels with indirect accesses by comparing against baseline LegUp 5.0 targeting a Xilinx VC707 board. For synthetic indexing at 256 threads, we observe an improvement of 150× LUTs, 4-5×— Fmax, 15-16×— II for UNIFORM RANDOM indexing. For real-world case studies such as Sparse Matrix-Vector multiplication, Graph Analytics and 1-D FFT, we see 5-20×— speedups for 16-256 threads with a 20-30% overhead for adding the NoC infrastructure.
Predictors and consequences of sudden gains in transdiagnostic cognitive-behavioural therapy for anxiety disorders

ABSTRACT Sudden gains—substantial stable symptom improvements between consecutive therapy sessions—are a common phenomenon. As condensed points of change, examination of sudden gains can provide insight into mechanisms of therapeutic change. This study investigated the association between sudden gains and cognitive change, therapeutic alliance, and/or client engagement in transdiagnostic group cognitive-behavioural therapy for anxiety disorders. Of 58 treatment initiators, 21% (n = 12) exhibited a sudden gain. Consistent with previous research, sudden gainers demonstrated significantly greater pre- to post-treatment symptom improvement than non-sudden gainers. Observational coding of therapy sessions found that sudden gains were associated with elevated levels of cognitive change and client engagement in the pre-gain session, and elevated levels of cognitive change and therapeutic alliance in the post-gain session. However, these results varied by use of within- and between-subject control comparisons, highlighting the value using a dual control methodology. In context of previous research, the results on cognitive change replicate previous findings in depressive populations, and clarify mixed findings in anxiety populations. The results on therapeutic alliance replicate previous findings for the first time in an anxiety sample, although the between-subject control comparisons revealed complexity previously undetected. This study was also the first to investigate and thus establish the relation between client engagement and sudden gains.
Improving Employee Voice About Transgressive or Disruptive Behavior: A Case Study

Purpose Employee voice plays an important role in organizational intelligence about patient safety hazards and other influences on quality of patient care. The authors report a case study of an academic medical center that aimed to understand barriers to voice and make improvements in identifying and responding to transgressive or disruptive behaviors. Method The case study focused on an improvement effort at Johns Hopkins Medicine that sought to improve employee voice using a two-phase approach of diagnosis and intervention. Confidential interviews with 67 individuals (20 senior leaders, 47 frontline personnel) were conducted during 2014 to diagnose causes of employee reluctance to give voice about behavioral concerns. A structured intervention program to encourage voice was implemented, 2014–2016, in response to the findings. Results The diagnostic interviews identified gaps between espoused policies of encouraging employee voice and what happened in practice. A culture of fear pervaded the organization that, together with widespread perceptions of futility, inhibited personnel from speaking up about concerns. The intervention phase involved four actions: sharing the interview findings; coordinating and formalizing mechanisms for identifying and dealing with disruptive behavior; training leaders in encouraging voice; and building capacity for difficult conversations. Conclusions The problems of giving voice are widely known across the organizational literature but are difficult to address. This case study offers an approach that includes diagnostic and intervention phases that may be helpful in remaking norms, facilitating employee voice, and improving organizational response. It highlights specific actions that are available for other organizations to adapt and test.
Safe Exploration in Markov Decision Processes with Time-Variant Safety using Spatio-Temporal Gaussian Process

In many real-world applications (e.g., planetary exploration, robot navigation), an autonomous agent must be able to explore a space with guaranteed safety. Most safe exploration algorithms in the field of reinforcement learning and robotics have been based on the assumption that the safety features are a priori known and time-invariant. This paper presents a learning algorithm called ST-SafeMDP for exploring Markov decision processes (MDPs) that is based on the assumption that the safety features are a priori unknown and time-variant. In this setting, the agent explores MDPs while constraining the probability of entering unsafe states defined by a safety function being below a threshold. The unknown and time-variant safety values are modeled using a spatio-temporal Gaussian process. However, there remains an issue that an agent may have no viable action in a shrinking true safe space. To address this issue, we formulate a problem maximizing the cumulative number of safe states in the worst case scenario with respect to future observations. The effectiveness of this approach was demonstrated in two simulation settings, including one using real lunar terrain data.
Multimodal neural pronunciation modeling for spoken languages with logographic origin

Graphemes of most languages encode pronunciation, though some are more explicit than others. Languages like Spanish have a straightforward mapping between its graphemes and phonemes, while this mapping is more convoluted for languages like English. Spoken languages such as Cantonese present even more challenges in pronunciation modeling: (1) they do not have a standard written form, (2) the closest graphemic origins are logographic Han characters, of which only a subset of these logographic characters implicitly encodes pronunciation. In this work, we propose a multimodal approach to predict the pronunciation of Cantonese logographic characters, using neural networks with a geometric representation of logographs and pronunciation of cognates in historically related languages. The proposed framework improves performance by 18.1% and 25.0% respective to unimodal and multimodal baselines.
Flow does not alter eNOS phosphoryation at Ser1179 or Thr495 in preconstricted mouse mesenteric arteries

In arteries, endothelium‐dependent vasodilatory agonists and flow‐induced shear stress cause vasodilation largely by activation of the endothelial enzyme eNOS, which generates nitric oxide that relaxes vascular smooth muscle. Agonists activate eNOS in part through increased phosphorylation at Ser1179 and decreased phosphorylation at Thr495. We previously found that preconstriction of intact, isolated mouse mesenteric arteries with phenylephrine also caused increased Ser1179 and decreased Thr495 eNOS phosphorylation, and sequential treatment with the vasodilatory agonist acetylcholine did not cause any further change in phosphorylation at these sites, despite producing vasodilation. The present study tests the hypothesis that luminal flow in these arteries preconstricted with phenylephrine also produces vasodilation without phosphorylation changes at these sites. First‐order mesenteric arteries, isolated from male C57/BL6 mice (7–20 weeks of age) anesthetized with pentobarbital (50 mg/kg, i.p.), were cannulated, pressurized, and treated with stepped increases in luminal flow (15–120 μL/min). Flow resulted in dilation that plateaued at ~60 μL/min (31.3 ± 3.0% dilation) and was significantly (P < 0.001) NOS‐dependent at all flow rates (determined by 10−4 mol/L L‐NAME treatment). In separate arteries, preconstriction with phenylephrine (10−5 mol/L) resulted in increased eNOS phosphorylation at Ser1179 (P < 0.05) and decreased phosphorylation at Thr495, but subsequent flow at 60 μL/min for 5 or 15 min did not cause further changes in phosphorylation, despite causing dilation. Thus, flow‐induced dilation does not require changes in these eNOS phosphorylation sites beyond those induced by alpha1‐adrenergic stimulation with phenylephrine, indicating that eNOS is activated by other mechanisms during acute flow‐induced dilation of preconstricted arteries.
Adaptive Process Model Matching - Improving the Eectiveness of Label-based Matching through Automated Configuration and Expert Feedback

Organizations often store information about their process landscape in large process model collections. To utilize those knowledge bases, process model matchers assist experts in keeping track of model relationships by automatically identifying corresponding activities. Yet, state-of-the-art matchers achieve an overall low effectiveness. That is, their results contain only a few existing, but many non-existing correspondences. Hence, practical application is far from being realized. In light of this, the thesis introduces ADBOT, an interactive matching technique that analyzes manually corrected matcher results to adapt itself to the characteristics of the respective model collection. At heart, ADBOT relies on BOT and OPBOT. BOT is a configurable matcher that solely examines activity labels and OPBOT analyzes model collection characteristics to automatically configure BOT without human intervention. While the three matchers pose different requirements on model and feedback availability, they all achieve a high effectiveness in relation to the state-of-the-art, as shown in a comparative evaluation. ADBOT as the most effective technique even yields improvements of up to 70%.
Utility of TERT Promoter Mutations for Cutaneous Primary Melanoma Diagnosis

Abstract: Telomerase reverse transcriptase (TERT) promoter mutations are commonly found in malignant melanomas but rare in melanocytic nevi. To assess its potential diagnostic utility for the distinction of melanoma from nevus, we determined the TERT promoter mutation status of 86 primary melanomas, 72 melanocytic nevi, and 40 diagnostically problematic melanocytic proliferations. Of the 86 melanomas, 67 (77.9%) were TERT-positive, defined as harboring a hotspot TERT promoter mutation at positions -124C>T, -124_125CC>TT, -138_139CC>TT, or -146C>T. Of the 72 nevi, only 1 (1.4%) was TERT-positive. Of the 40 diagnostically uncertain melanocytic proliferations, 2 (5.0%) were TERT-positive. TERT positivity as a test for melanoma versus nevus had an accuracy of 87.3% [95% confidence interval (CI), 81.1–92.1], a sensitivity of 77.9% (95% CI, 68.9–85.4), a specificity of 98.6% (95% CI, 95.8–100), a positive predictive value of 98.5% (95% CI, 95.6–100), and a negative predictive value of 78.9% (95% CI, 72.6–85.4). Our results indicate that hotspot TERT promoter mutation status may be a useful ancillary parameter for the diagnosis of melanoma. In particular, the high specificity of these mutations for melanoma indicates the presence of a TERT promoter mutation in a melanocytic neoplasm associated with diagnostic controversy, or uncertainty should increase concern for a melanoma.
The fine structure of blood follicles in the earthworm genera Amynthas and Lumbricus (Annelida: Oligochaeta)

Blood follicles of the earthworm Amynthas are hemoglobin‐containing, sac‐like dilatations of blood vessels which connect to the general circulation. Grape‐like clusters of follicles are found posterior to the pharynx, among tufts of micronephridia, and single follicles are located among cells of the pharyngeal gland. In Lumbricus, follicles take the form of simple swellings and irregular‐shaped diverticula of nephridial capillaries.
1.2 Tbps/cm2 Enabling Silicon Photonics IC Technology Based on 40-nm Generation Platform

Optical transmitter and receiver ICs, each with a footprint of ${\text{25 mm}}^{2}$, were fabricated using a silicon photonics platform based on 40-nm-node CMOS technology. High-speed transmissions of data at 300 Gbps were demonstrated. The wire-type waveguide (WG) in the transmitter IC had a width of 350 nm and a height of 200 nm, and in the completed optical IC, it showed low propagation loss (1.62 dB/cm) for the O-band transverse electric mode and low propagation loss variation (0.15 dB/cm) at 3σ. The coupling loss of the grating couplers was reduced to 2.7 dB by using an apodization structure with a narrow trench width of 70 nm. The wafer-scale reproducibility of the WG width was excellent, as confirmed by a spectral variation analysis using a large number of the microring resonators. The surface-illumination photodetectors (PDs) of the optical receiver were made using a germanium epitaxial film and had a leakage current of less than 10 nA at 3 V and a responsivity of 0.75 A/W. The modulation efficiency of the PN-junction-type Mach–Zehnder modulators of the optical transmitter was 1.3 V⋅cm at 0 V. The uniformity of the PDs and modulators on a 300-mm wafer was very high. By using the fabricated optical transmitter and receiver ICs, data transmissions at up to 12 × 25 Gbps in the O band (1.3 μm) were demonstrated. Furthermore, low-loss filtering operation in 1:4 channel delayed interferometer-based demultiplexing was shown to enable even faster data transmissions. These results indicate that our silicon photonics platform is very useful for fabricating wideband optical ICs.
Triggered-Issuance and Triggered-Execution: A Control Paradigm to Minimize Pipeline Stalls in Distributed Controlled Coarse-Grained Reconfigurable Arrays

Distributed controlled coarse-grained reconfigurable arrays (CGRAs) enable efficient execution of irregular control flows by reconciling divergence in the processing elements (PEs). To further improve performance by better exploiting spatial parallelism, the triggered instruction architecture (TIA) eliminates the program counter and branch instructions by converting control flows into predicate dependencies as triggers. However, pipeline stalls, which occur in pipelines composed of both intra and inter-PEs, remain a major obstacle to the overall performance. In fact, the stalls in distributed controlled CGRAs pose a unique problem that is difficult to resolve by previous techniques. This work presents a triggered-issuance and triggered-execution (TITE) paradigm in which the issuance and execution of instructions are separately triggered to further relax the predicate dependencies in TIA. In this paradigm, instructions are paired as dual instructions to eliminate stalls caused by control divergence. Tags that identify the data transmitted between PEs are forwarded for acceleration. As a result, pipeline stalls of both intra- and inter-PEs can be significantly minimized. Experiments show that TITE improves performance by 21 percent, energy efficiency by 17 percent, and area efficiency by 12 percent compared with a baseline TIA.