Miracle-dz/UniFAR-FTUs huggingface dataset:
Composite, haustellate mouthparts in netwinged beetle and firefly larvae (Coleoptera, Cantharoidea: Lycidae, Lampyridae)

During lycid embryogenesis, labral and mandibular anlagen develop separately. Each anterolateral corner of the labrum elongates into a stylet, while the whole of each mandible involutes into a flute that is open to the lateral aspects. The stylets and flutes interlock in such a way as to leave canals, fashioning left and right haustellate apparatuses. During lampyrid embryogenesis, only one pair of anlagen forms instead of two. The pair matures into sharp, arcuate appendages that appear to be typical mandibles, but nevertheless a canal forms internally. The canal is not formed by coadaptation of two appendages; instead, cells within the pair create the canal autonomously. Indications are that the canal is homologous between these two families. It is suggested that in lampyrids, labral and mandibular cell fields develop together in the same anlage but behave according to their own respective programs, forming the canal with morphogenetic movements that are comparable to those of lycids. © 1994 Wiley‐Liss, Inc.
Geographical and Historical Patterns in the Emergences of Novel Highly Pathogenic Avian Influenza (HPAI) H5 and H7 Viruses in Poultry

Over the years, the emergence of novel H5 and H7 highly pathogenic avian influenza viruses (HPAI) has been taking place through two main mechanisms: first, the conversion of a low pathogenic into a highly pathogenic virus, and second, the reassortment between different genetic segments of low and highly pathogenic viruses already in circulation. We investigated and summarized the literature on emerging HPAI H5 and H7 viruses with the aim of building a spatio-temporal database of all these recorded conversions and reassortments events. We subsequently mapped the spatio-temporal distribution of known emergence events, as well as the species and production systems that they were associated with, the aim being to establish their main characteristics. From 1959 onwards, we identified a total of 39 independent H7 and H5 LPAI to HPAI conversion events. All but two of these events were reported in commercial poultry production systems, and a majority of these events took place in high-income countries. In contrast, a total of 127 reassortments have been reported from 1983 to 2015, which predominantly took place in countries with poultry production systems transitioning from backyard to intensive production systems. Those systems are characterized by several co-circulating viruses, multiple host species, regular contact points in live bird markets, limited biosecurity within value chains, and frequent vaccination campaigns that impose selection pressures for emergence of novel reassortants. We conclude that novel HPAI emergences by these two mechanisms occur in different ecological niches, with different viral, environmental and host associated factors, which has implications in early detection and management and mitigation of the risk of emergence of novel HPAI viruses.
Real-time Voltage Regulation in Distribution Systems via Decentralized PV Inverter Control

We consider the decentralized reactive power control of photovoltaic (PV) inverters spread throughout a radial distribution network. Our objective is to minimize the expected voltage regulation error, while guaranteeing the robust satisfaction of distribution system voltage magnitude and PV inverter capacity constraints. Our approach entails the offline design and the online implementation of the decentralized controller. In the offline control design, we compute the decentralized controller through the solution of a robust convex program. Under the restriction that the decentralized controller have an affine disturbance feedback form, the optimal solution of the decentralized control design problem can be computed via the solution of a finite-dimensional conic program. In the online implementation, we provide a method to implement the decentralized controller at a timescale that is fast enough to counteract the fluctuations in the system disturbance process. The resulting trajectories of PV inverter reactive power injections and nodal voltage magnitudes are guaranteed to be feasible for any realization of the system disturbance under the proposed controller. We demonstrate the ability of the proposed decentralized controller to effectively regulate voltage over a fast timescale with a case study of the IEEE 123-node test feeder.
Spark-MPI: Approaching the Fifth Paradigm of Cognitive Applications

Over the past decade, the fourth paradigm of data-intensive science rapidly became a major driving concept of multiple application domains encompassing and generating large-scale devices such as light sources and cutting edge telescopes. The success of data-intensive projects subsequently triggered the next generation of machine learning approaches. These new artificial intelligent systems clearly represent a paradigm shift from data processing pipelines towards the fifth paradigm of composite cognitive applications requiring the integration of Big Data processing platforms and HPC technologies. The paper addresses the existing impedance mismatch between data-intensive and compute-intensive ecosystems by presenting the Spark-MPI approach based on the MPI Exascale Process Management Interface (PMIx). The approach is demonstrated within the context of hybrid MPI/GPU ptychographic image reconstruction pipelines and distributed deep learning applications.
Coordinated Dispatch of Virtual Energy Storage Systems in LV Grids for Voltage Regulation

The growth in installed solar photovoltaic (PV) capacity and the ever-increasing power demand due to the use of energy-hungry appliances have caused voltage issues. In this paper, a hierarchical dispatch strategy is proposed for coordinating multiple groups of virtual energy storage systems (VESSs), i.e., residential houses with air conditioners, to regulate voltage in low-voltage (LV) grids with high solar PV penetration. Specifically, the two levels of the proposed model are: 1) in the lower level, VESSs within each intelligent residential district are controlled locally by individual aggregator; 2) in the upper level, multiple aggregators are coordinated to achieve voltage regulation through a consensus control strategy. By exchanging information through sparse communication links, each aggregator shares the required active power adjustment among all participating groups, without compromising users’ thermal comfort. Simulation result demonstrates that the proposed control scheme can effectively regulate voltage in LV grids with greater robustness and scalability.
CpxR/CpxA Controls scsABCD Transcription To Counteract Copper and Oxidative Stress in Salmonella enterica Serovar Typhimurium

Copper intoxication triggers both specific and nonspecific responses in Salmonella. The scs locus, which codes for periplasmic thiol/disulfide-oxidoreductase/isomerase-like proteins, has been the focus of attention because it is necessary for copper resistance, oxidative stress responses, and virulence and because it is not present in nonpathogenic Escherichia coli. Still, the conditions under which the scs locus is expressed and the roles of its individual components remain unknown. In this report, we examine the contribution of each Scs factor to survival under H2O2 and copper stress. We establish that the scs genes form a copper-activated operon controlled by the CpxR/CpxA signal transduction system, and we provide evidence of its conserved gene arrangement and regulation in other bacterial pathogens. ABSTRACT Periplasmic thiol/disulfide oxidoreductases participate in the formation and isomerization of disulfide bonds and contribute to the virulence of pathogenic microorganisms. Among the systems encoded in the Salmonella genome, the system encoded by the scsABCD locus was shown to be required to cope with Cu and H2O2 stress. Here we report that this locus forms an operon whose transcription is driven by a promoter upstream of scsA and depends on CpxR/CpxA and on Cu. Furthermore, genes homologous to scsB, scsC, and scsD are always detected immediately downstream of scsA and in the same genetic arrangement in all scsA-harboring enterobacterial species. Also, a CpxR-binding site is detected upstream of scsA in most of those species, providing evidence of evolutionarily conserved function and regulation. Each individual scs gene shows a different role in copper and/or H2O2 resistance, indicating hierarchical contributions of these factors in the defense against these intoxicants. A protective effect of Cu preincubation against H2O2 toxicity and the increased Cu-mediated activation of cpxP in the ΔscsABCD mutant suggest that the CpxR/CpxA-controlled transcription of the ScsABCD system contributes to prevent Cu toxicity and to restore the redox balance at the Salmonella envelope. IMPORTANCE Copper intoxication triggers both specific and nonspecific responses in Salmonella. The scs locus, which codes for periplasmic thiol/disulfide-oxidoreductase/isomerase-like proteins, has been the focus of attention because it is necessary for copper resistance, oxidative stress responses, and virulence and because it is not present in nonpathogenic Escherichia coli. Still, the conditions under which the scs locus is expressed and the roles of its individual components remain unknown. In this report, we examine the contribution of each Scs factor to survival under H2O2 and copper stress. We establish that the scs genes form a copper-activated operon controlled by the CpxR/CpxA signal transduction system, and we provide evidence of its conserved gene arrangement and regulation in other bacterial pathogens.
Impacts of Haze on Housing Prices: An Empirical Analysis Based on Data from Chengdu (China)

Based on cross-section data of 20 districts in Chengdu, this article reviews the relationships between haze and housing prices with the combined application of Spatial Error Model (SEM) and Spatial Lag Model (SLM). The results illustrate that haze significantly have negative impacts on both the selling and rental prices of houses. Controlling other variables, if the air quality index rises by 0.1, the housing selling prices and rental prices will drop by 3.97% and 4.01%, respectively. Interestingly, housing rental prices have a more significant response to the air quality than housing sale prices. Residents are willing to pay a premium for better air quality and the influence of air quality is partially reflected in housing prices, which indicates that better air quality has been becoming a scarce resource with the improvement of people’s living standard. Furthermore, the impacts of haze on housing prices are also expected to lead to a “crowding out effect” in different regions. This would be detrimental for human capital accumulation and will accelerate the regional divergence in the internal economy and population structure, thus forming a region “fence” within cities.
Distinguishing malignant from benign microscopic skin lesions using desorption electrospray ionization mass spectrometry imaging

Significance Timely detection of microscopic tumors is of utmost importance in cancer diagnostics. We show that desorption electrospray ionization mass spectrometry imaging (DESI-MSI) can successfully locate microscopic aggregates of a common skin cancer, basal cell carcinoma (BCC), and distinguish them from adjacent normal skin. DESI-MSI unveils an altered chemical profile in BCC region, including lipids and metabolites, and does not rely on visual identification of histopathologic features. We processed specimens from 86 Mohs micrographic surgeries, with nearly 60% of tumors sized less than 1 mm in diameter. By applying the statistical method of least absolute shrinkage and selection operator (Lasso) on collected DESI-MSI data, we were able to achieve up to 94.1% diagnostic accuracy compared with pathological evaluation of BCC. Detection of microscopic skin lesions presents a considerable challenge in diagnosing early-stage malignancies as well as in residual tumor interrogation after surgical intervention. In this study, we established the capability of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to distinguish between micrometer-sized tumor aggregates of basal cell carcinoma (BCC), a common skin cancer, and normal human skin. We analyzed 86 human specimens collected during Mohs micrographic surgery for BCC to cross-examine spatial distributions of numerous lipids and metabolites in BCC aggregates versus adjacent skin. Statistical analysis using the least absolute shrinkage and selection operation (Lasso) was employed to categorize each 200-µm-diameter picture element (pixel) of investigated skin tissue map as BCC or normal. Lasso identified 24 molecular ion signals, which are significant for pixel classification. These ion signals included lipids observed at m/z 200–1,200 and Krebs cycle metabolites observed at m/z < 200. Based on these features, Lasso yielded an overall 94.1% diagnostic accuracy pixel by pixel of the skin map compared with histopathological evaluation. We suggest that DESI-MSI/Lasso analysis can be employed as a complementary technique for delineation of microscopic skin tumors.
Forward-back and back-forward drivable controls for human-robot interaction

In previous research, the back-forward drivability of load-side torque control system based on a motor-side acceler­ation control has proven to be high, but contact motion has not yet been realized in human-robot interaction such as powered exoskeleton and direct teaching. To address this issue, this study proposes a load-side torque control system that achieves both bouncing suppression and human-interaction. This paper focuses on load-side acceleration because the bouncing motion at environmental contact and the human-robot interaction motion are able to be evaluated to its performances intuitively. Human-robot interaction is applied in low-frequency, and bouncing suppression is applied in high-frequency. The experimental results verify the effectiveness of the proposed method.
User Association in Millimeter Wave MIMO Networks

User association is necessary in dense millimeter wave (mmWave) networks to determine which base station a user connects to in order to balance base station loads and maximize throughput. Given that mmWave connections are highly directional and vulnerable to small channel variations, user association changes these connections and hence significantly affects the user's instantaneous rate as well as network interference. In this paper, we introduce a new load balancing user association scheme for mmWave MIMO networks which considers this dependency on user association of user's transmission rates and network interference. We formulate the user association problem as mixed integer nonlinear programming and design a polynomial-time algorithm, called Worst Connection Swapping (WCS), to find a near-optimal solution. Simulation results confirm that the proposed user association scheme improves network performance significantly by moving the traffic of congested base stations to lightly-loaded ones and adjusting the interference accordingly. Further, the proposed WCS algorithm outperforms other generic algorithms for combinatorial programming such as the genetic algorithm in both accuracy and speed at several orders of magnitude faster, and for small networks where exhaustive search is possible it reaches the optimal solution.
A compact dual-band antenna including symmetrical slots for 2.45/5.8 GHz handheld RFID reader applications

A novel miniaturized dual-band slotted patch antenna for radio frequency identification (RFID) applications in the microwave band (2.45 and 5.8 GHz) has been proposed. It consists of patch excited by a 50 ohms microstrip-line on the top layer, and a rectangular ground plane on the bottom layer. They are made of a perfect electrical conductors. The antenna has an overall size of 26×28mm2 and set on an FR4 substrate with constant dielectric permittivity 4.3, thickness of 1.6mm and loss tangent of 0.025. The antenna is designed with acceptable gain, low profile and cheap cost achievement. A good impedance bandwidth of 106 MHz has been achieved from 2.39 to 2.496 GHz for the lower band, while the upper band covers 579 MHz (from 5.585 to 6.164 GHz). The gain obtained into simulation of this antenna is 2.09 dB at 2.45GHz and 3.51 dB at 5.8 GHz. The proposed antenna is a great candidate for universal microwave RFID applications. The simulation results was achieved by using CST Microwave Studio electromagnetic and high frequency structural simulator (HFSS) solvers.
Combining Short-Term Interval Training with Caloric Restriction Improves ß-Cell Function in Obese Adults

Although low-calorie diets (LCD) improve glucose regulation, it is unclear if interval exercise (INT) is additive. We examined the impact of an LCD versus LCD + INT training on ß-cell function in relation to glucose tolerance in obese adults. Twenty-six adults (Age: 46 ± 12 year; BMI 38 ± 6 kg/m2) were randomized to 2-week of LCD (~1200 kcal/day) or energy-matched LCD + INT (60 min/day alternating 3 min at 90 and 50% HRpeak). A 2 h 75 g oral glucose tolerance test (OGTT) was performed. Insulin secretion rates (ISR) were determined by deconvolution modeling to assess glucose-stimulated insulin secretion ([GSIS: ISR/glucose total area under the curve (tAUC)]) and ß-cell function (Disposition Index [DI: GSIS/IR]) relative to skeletal muscle (Matsuda Index), hepatic (HOMA-IR) and adipose (Adipose-IRfasting) insulin resistance (IR). LCD + INT, but not LCD alone, reduced glucose and total-phase ISR tAUC (Interactions: p = 0.04 and p = 0.05, respectively). Both interventions improved skeletal muscle IR by 16% (p = 0.04) and skeletal muscle and hepatic DI (Time: p < 0.05). Improved skeletal muscle DI was associated with lower glucose tAUC (r = −0.57, p < 0.01). Thus, LCD + INT improved glucose tolerance more than LCD in obese adults, and these findings relate to ß-cell function. These data support LCD + INT for preserving pancreatic function for type 2 diabetes prevention.
Audio Visual Scene-Aware Dialog (AVSD) Challenge at DSTC7

Scene-aware dialog systems will be able to have conversations with users about the objects and events around them. Progress on such systems can be made by integrating state-of-the-art technologies from multiple research areas including end-to-end dialog systems visual dialog, and video description. We introduce the Audio Visual Scene Aware Dialog (AVSD) challenge and dataset. In this challenge, which is one track of the 7th Dialog System Technology Challenges (DSTC7) workshop1, the task is to build a system that generates responses in a dialog about an input video
Multi-Cast Attention Networks for Retrieval-based Question Answering and Response Prediction

Attention is typically used to select informative sub-phrases that are used for prediction. This paper investigates the novel use of attention as a form of feature augmentation, i.e, casted attention. We propose Multi-Cast Attention Networks (MCAN), a new attention mechanism and general model architecture for a potpourri of ranking tasks in the conversational modeling and question answering domains. Our approach performs a series of soft attention operations, each time casting a scalar feature upon the inner word embeddings. The key idea is to provide a real-valued hint (feature) to a subsequent encoder layer and is targeted at improving the representation learning process. There are several advantages to this design, e.g., it allows an arbitrary number of attention mechanisms to be casted, allowing for multiple attention types (e.g., co-attention, intra-attention) and attention variants (e.g., alignment-pooling, max-pooling, mean-pooling) to be executed simultaneously. This not only eliminates the costly need to tune the nature of the co-attention layer, but also provides greater extents of explainability to practitioners. Via extensive experiments on four well-known benchmark datasets, we show that MCAN achieves state-of-the-art performance. On the Ubuntu Dialogue Corpus, MCAN outperforms existing state-of-the-art models by $9\%$. MCAN also achieves the best performing score to date on the well-studied TrecQA dataset.
On the Computational Complexity of Blind Detection of Binary Linear Codes

In this work, we study the computational complexity of the Minimum Distance Code Detection problem. In this problem, we are given a set of noisy codeword observations and we wish to find a code in a set of linear codes $\mathcal{C}$ of a given dimension k, for which the sum of distances between the observations and the code is minimized. We prove that, for the practically relevant case when the set $\mathcal{C}$ only contains a fixed number of candidate linear codes, the detection problem is NP-hard and we identify a number of interesting open questions related to the code detection problem.
How to Make Profit: Exploiting Fluctuating Electricity Prices with Albatross, A Runtime System for Heterogeneous HPC Clusters

The ongoing evolution of the power grid towards a highly dynamic supply system poses challenges as renewables induce new grid characteristics. The volatility of electricity sources leads to a fluctuating electricity price, which even becomes negative when excess supply occurs. Operators of high-performance--computing (HPC) clusters therefore can consider the highly dynamic variations of electricity prices to provide an energy-efficient and economic operation. This paper presents Albatross, a runtime system for heterogeneous HPC clusters. To ensure an energy-efficient and economic processing of HPC workloads, our system exploits heterogeneity at the hardware level and considers dynamic electricity prices. We have implemented Albatross and evaluate it on a heterogeneous HPC cluster in our lab to show how the power demand of the cluster decreases when electricity prices are high (i.e., excess demand at the grid). When electricity prices are low or negative (i.e., excess supply to the grid), Albatross purposefully increases the workload and, thus, power demand of the HPC cluster---to make profit.
Incorporating Side Information by Adaptive Convolution – Supplementary Material

Camera extrinsic parameters, such as camera tilt angle and camera height, are useful types of side information for crowd counting. The camera tilt angle affects a person’s appearance, while the distance affects the scale. Note that the camera tilt angle/height can be used to estimate the perspective map, whose values indicate the size of a person appearing at each location. As existing datasets do not contain the side information of extrinsic camera parameters, here we collect a new dataset consisting of indoor/outdoor scenes from various camera angles and heights. The scenes were captured using a smartphone camera, which was placed on a tripod to keep it stable. The camera tilt angle was recorded using the accelerometer tilt-sensor of the smartphone, and the height of the camera to the ground-plane was measured using a laser range finder. The perspective map for each scene is estimated from the camera extrinsic parameters.