Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimal operation of energy storage systems considering forecasts and battery degradation

Energy storage systems have the potential to deliver value in multiple ways, and these must be traded off against one another. An operational strategy that aims to maximize the returned value of such a system can often be significantly improved with the use of forecasting — of demand, generation, and pricing — but consideration of battery degradation is important too. This paper proposes a stochastic dynamic programming approach to optimally operate an energy storage system across a receding horizon. The method operates an energy storage asset to deliver maximal lifetime value, by using available forecasts and by applying a multi-factor battery degradation model that takes into account operational impacts on system degradation. Applying the method to a dataset of a residential Australian customer base demonstrates that an optimally operated system returns a lifetime value which is 160% more, on average, than that of the same system operated using a set-point-based method applied in many settings today.
The role-relevance model for enhanced semantic targeting in unstructured text

Personalized search provides a potentially powerful tool, however, it is limited due to the large number of roles that a person has: parent, employee, consumer, etc. We present the role-relevance algorithm: a search technique that favors search results relevant to the user’s current role. The role-relevance algorithm uses three factors to score documents: (1) the number of keywords each document contains; (2) each document’s geographic relevance to the user’s role (if applicable); and (3) each document’s topical relevance to the user’s role (if applicable). Results on a pre-labeled corpus show an average improvement in search precision of approximately 20% compared to keyword search alone. We further consider several extensions to this algorithm.
Robust concurrency control in main-memory DBMS: What main memory giveth, the application taketh away

Modern systems with large main memories and massively parallel processors have inspired many new high-performance OLTP systems [2–4,6], often referred to as main memory DBMS (MMDBMS). These systems leverage spacious main memory to ﬁt the whole working set in DRAM with streamlined, memory-friendly data structures; further, optimizations for multicore and multi-socket hardware allow a much higher level of parallelism compared to conventional database systems. With disk overheads and delays removed, transaction latencies drop precipitously and worker threads can usually execute transactions to completion without interruption. The result is a welcome reduction in contention and less pressure on whatever concurrency control (CC) scheme might be in place.
Extracorporeal Membrane Oxygenation and the Kidney

Background: Extracorporeal membrane oxygenation (ECMO) is an effective therapy for patients with reversible cardiac and/or respiratory failure. Acute kidney injury (AKI) often occurs in patients supported with ECMO; it frequently evolves into chronic kidney damage or end-stage renal disease and is associated with a reported 4-fold increase in mortality rate. Although AKI is generally due to the hemodynamic alterations associated with the baseline disease, ECMO itself may contribute to maintaining kidney dysfunction through several mechanisms. Summary: AKI may be related to conditions derived from or associated with extracorporeal therapy, leading to a reduction in renal oxygen delivery and/or to inflammatory damage. In particular, during pathological conditions requiring ECMO, the biological defense mechanisms maintaining central perfusion by a reduction of perfusion to peripheral organs (such as the kidney) have been identified as pretreatment and patient-related risk factors for AKI. Hormonal pathways are also impaired in patients supported with ECMO, leading to failures in mechanisms of renal homeostasis and worsening fluid overload. Finally, inflammatory damage, due to the primary disease, heart and lung crosstalk with the kidney or associated with extracorporeal therapy itself, may further increase the susceptibility to AKI. Renal replacement therapy can be integrated into the main extracorporeal circuit during ECMO to provide for optimal fluid management and removal of inflammatory mediators. Key Messages: AKI is frequently observed in patients supported with ECMO. The pathophysiology of the associated AKI is chiefly related to a reduction in renal oxygen delivery and/or to inflammatory damage. Risk factors for AKI are associated with a patient's underlying disease and ECMO-related conditions.
Learning Deconvolutional Network for Object Tracking

Object tracking can be tackled by learning a model of tracking the target’s appearance sequentially. Therefore, robust appearance representation is a critical step in visual tracking. Recently, deep convolution network has demonstrated remarkable ability in visual tracking via leveraging robust high-level features. To obtain these high-level features, convolution and pooling operations are executed alternatively in deep convolution network. However, these operations lead to low spatial resolution feature maps which degrade the localization precision in tracking. While low level features have sufficient spatial resolution, their representation ability is insufficient. To mitigate this issue, we exploited deconvolution network in visual tracking. This deconvolution network works as a learnable upsampling layer which takes low-resolution high-level feature maps as input and outputs enlarged feature maps. Meanwhile, the low level feature maps are fused with these high level feature maps via a summarization operation to better represent target appearance. We formulate the network training as a regression issue and train this network end to end. Extensive experiments on two tracking benchmarks demonstrate the effectiveness of our method.
On Protostellar Disks in Herbig Ae/Be Stars

The spectral shape of IR emission from Herbig Ae/Be stars has been invoked as evidence for accretion disks around high-mass protostars. Instead, we present here models based on spherical envelopes with an r-1.5 dust density profile that successfully explain the observed spectral shapes. The spectral energy distributions of eight primary candidates for protostellar disks are fitted in detail for all wavelengths available, from visual to far-IR. The only envelope property adjusted in individual sources is the overall visual optical depth, and it ranges from 0.3 to 3. In each case, our models properly reproduce the data for IR excess, visual extinction, and reddening. The success of our models shows that accretion disks cannot make a significant contribution to the radiation observed in these pre-main-sequence stars.
Generalized matrix completion and algebraic natural proofs

Algebraic natural proofs were recently introduced by Forbes, Shpilka and Volk (Proc. of the 49th Annual ACM SIGACT Symposium on Theory of Computing (STOC), pages 653–664, 2017) and independently by Grochow, Kumar, Saks and Saraf (CoRR, abs/1701.01717, 2017) as an attempt to transfer Razborov and Rudich’s famous barrier result (J. Comput. Syst. Sci., 55(1): 24–35, 1997) for Boolean circuit complexity to algebraic complexity theory. Razborov and Rudich’s barrier result relies on a widely believed assumption, namely, the existence of pseudo-random generators. Unfortunately, there is no known analogous theory of pseudo-randomness in the algebraic setting. Therefore, Forbes et al. use a concept called succinct hitting sets instead. This assumption is related to polynomial identity testing, but it is currently not clear how plausible this assumption is. Forbes et al. are only able to construct succinct hitting sets against rather weak models of arithmetic circuits. Generalized matrix completion is the following problem: Given a matrix with affine linear forms as entries, find an assignment to the variables in the linear forms such that the rank of the resulting matrix is minimal. We call this rank the completion rank. Computing the completion rank is an NP-hard problem. As our first main result, we prove that it is also NP-hard to determine whether a given matrix can be approximated by matrices of completion rank ≤ b. The minimum quantity b for which this is possible is called border completion rank (similar to the border rank of tensors). Naturally, algebraic natural proofs can only prove lower bounds for such border complexity measures. Furthermore, these border complexity measures play an important role in the geometric complexity program. Using our hardness result above, we can prove the following barrier: We construct a small family of matrices with affine linear forms as entries and a bound b, such that at least one of these matrices does not have an algebraic natural proof of polynomial size against all matrices of border completion rank b, unless coNP ⊆ ∃ BPP. This is an algebraic barrier result that is based on a well-established and widely believed conjecture. The complexity class ∃ BPP is known to be a subset of the more well known complexity class in the literature. Thus ∃ BPP can be replaced by MA in the statements of all our results. With similar techniques, we can also prove that tensor rank is hard to approximate. Furthermore, we prove a similar result for the variety of matrices with permanent zero. There are no algebraic polynomial size natural proofs for the variety of matrices with permanent zero, unless P#P ⊆ ∃ BPP. On the other hand, we are able to prove that the geometric complexity theory approach initiated by Mulmuley and Sohoni (SIAM J. Comput. 31(2): 496–526, 2001) yields proofs of polynomial size for this variety, therefore overcoming the natural proofs barrier in this case.
High frequency LLC resonant converter with magnetic shunt integrated planar transformer

High Frequency LLC requires a smaller resonant inductance which is usually implemented by transformer leakage inductance. However, this small resonant inductance is difficult to deal with a wide input voltage range. This paper proposes a new method to implement a larger resonant inductance by using a magnetic shunt integrated into planar transformer. The switching frequency can be greatly narrowed by designing a smaller inductance ratio of magnetizing inductance to resonant inductance. Since this method can well deal with a wide input voltage range without adding extra inductor and increasing the size of the transformer, the power density can be improved. The precise leakage inductance calculation method for this transformer and detailed LLC converter design procedure are presented. A 280–380V and 48V–100W half bridge LLC resonant converter with 1 MHz resonant frequency is built to verify the design methodology.
Energy Management in a Network of Grid-Connected Microgrids/Nanogrids Using Compromise Programming

A new multi-objective optimization model is proposed for efficient integration of a group of microgrids/nanogrids with local energy storage devices into the power grid. In this model, the individual microgrids/nanogrids can exchange power locally among each other as well as with the external electricity grid. A pricing regime is introduced in which differences in the local and grid buy and sell time-of-use prices of electricity incentivize local inter-microgrid/nanogrid exchanges of power over power exchange with the grid. A novel formulation of a multiple-objective constrained optimization is presented for solving the microgrids/nanogrids energy management problem under the proposed electricity pricing regime. This approach is based on minimization of <inline-formula> <tex-math notation="LaTeX">$ {l_{1}}$ </tex-math></inline-formula> or <inline-formula> <tex-math notation="LaTeX">$ {l_{2}}$ </tex-math></inline-formula> distances of the microgrids/nanogrids cost vector to a utopia point in the solution space. Components of the utopia point are defined as the minimum cost achievable by the corresponding microgrid/nanogrid when it always uses the favorable local buy/sell prices. The proposed optimization models are in the form of convex linear/quadratic programs without any binary or integer variables for <inline-formula> <tex-math notation="LaTeX">$ {l_{1}}/ {l_{2}}$ </tex-math></inline-formula> norms. Results of numerical simulations with on-line rolling horizon optimization of the storage device power flow decisions demonstrate the effectiveness of the proposed methods.
Psychiatric aspects of the assessment and treatment of sex offenders

Training in general and forensic psychiatry in the assessment and treatment of sex offenders is in need of considerable improvement. Although most sex offenders are not mentally ill, many are subject to substance misuse, abnormal personality traits, personality disorder, learning disability or dysphoric mood, and in some organic factors will be involved. Comprehensive assessment of sex offenders includes a full history and mental state evaluation, obtaining a collateral history from other sources, observation, psychometric testing, and psychophysiological methods of assessment, including penile plethysmography. Trials of the use of the polygraph are also under way. The treatment of sex offenders, especially those with paraphilias, may include medication with selective serotonin reuptake inhibitors or anti-libidinal agents. Ethical considerations can be problematic, but a balance can often be found between the welfare of the offender and the safety of the public.
Self-Heating in Spray Dried Detergents

During the spray drying of detergent formulations, powder commonly accumulates on the inner walls of the spray drying tower. Under certain conditions, when these accumulations are large enough, self-heating can occur, whereby exothermic reactions within the accumulations cause an increase in the powder temperature within these layers. This can lead to unwanted charring and in severe cases to thermal runaway. This study aims to evaluate the methods for characterising the self-heating behaviour of these detergent powders. Firstly, two basket heating methods, namely the steady-state approach and cross-point temperature (CPT) method, were used to estimate the zero-order kinetics of the self-heating reaction of a typical detergent formulation. The resulting kinetics of these methods were not in agreement, with this being attributed to the CPT method’s sensitivity to errors. The kinetics estimated from these methods were used in a developed 2D-axismmetric transient model of heat and mass transfer within an oven heated basket of detergent powder. This was used to make temperature-time profile and critical ambient temperature (temperature above which thermal runaway occurs) predictions, and to simulate aspects of the basket heating experiments. A novel approach was developed using a combination of the basket experiments and the numerical model. This “parameter estimation approach” uses maximum likelihood estimations to estimate the required parameters. The model was fitted to experimentally measured temperature data, allowing the values of the powder thermal conductivity, specific heat capacity, and self-heating reaction kinetics could be estimated. Determining the specific heat capacity prior to fitting greatly improved the results. This approach was found to be considerably faster than the existing oven based methods (5 times faster than steady-state approach), determine more parameters, and improve greatly on the error of the estimated parameters (over 20 times more accurate than CPT method). An approach was presented showing how the findings of this research are applied in predicting self-heating in spray dryers for different tower temperatures, heat transfer coefficients, and build-up thicknesses.
Thor's Hammer: An Ungrounded Force Feedback Device Utilizing Propeller-Induced Propulsive Force

We present a new handheld haptic device, Thor's Hammer, which uses propeller propulsion to generate ungrounded, 3-DOF force feedback. Thor's Hammer has six motors and propellers that generates strong thrusts of air without the need for physical grounding or heavy air compressors. With its location and orientation tracked by an optimal tracking system, the system can exert forces in arbitrary directions regardless of the device's orientation. Our technical evaluation shows that Thor's Hammer can apply up to 4 N of force in arbitrary directions with less than 0.11 N and 3.9° of average magnitude and orientation errors. We also present virtual reality applications that can benefit from the force feedback provided by Thor's Hammer. Using these applications, we conducted a preliminary user study and participants felt the experience more realistic and immersive with the force feedback.
The Most Developmentally Truncated Fishes Show Extensive Hox Gene Loss and Miniaturized Genomes

Hox genes play a fundamental role in regulating the embryonic development of all animals. Manipulation of these transcription factors in model organisms has unraveled key aspects of evolution, like the transition from fin to limb. However, by virtue of their fundamental role and pleiotropic effects, simultaneous knockouts of several of these genes pose significant challenges. Here, we report on evolutionary simplification in two species of the dwarf minnow genus Paedocypris using whole genome sequencing. The two species feature unprecedented Hox gene loss and genome reduction in association with their massive developmental truncation. We also show how other genes involved in the development of musculature, nervous system, and skeleton have been lost in Paedocypris, mirroring its highly progenetic phenotype. Further, we identify two mechanisms responsible for genome streamlining: severe intron shortening and reduced repeat content. As a naturally simplified system closely related to zebrafish, Paedocypris provides novel insights into vertebrate development.
Looks Can Be Deceiving: Using Gaze Visualisation to Predict and Mislead Opponents in Strategic Gameplay

In competitive co-located gameplay, players use their opponents' gaze to make predictions about their plans while simultaneously managing their own gaze to avoid giving away their plans. This socially competitive dimension is lacking in most online games, where players are out of sight of each other. We conducted a lab study using a strategic online game; finding that (1) players are better at discerning their opponent's plans when shown a live visualisation of the opponent's gaze, and (2) players who are aware that their gaze is tracked will manipulate their gaze to keep their intentions hidden. We describe the strategies that players employed, to various degrees of success, to deceive their opponent through their gaze behaviour. This gaze-based deception adds an effortful and challenging aspect to the competition. Lastly, we discuss the various implications of our findings and its applicability for future game design.
The Ethnobot: Gathering Ethnographies in the Age of IoT

Computational systems and objects are becoming increasingly closely integrated with our daily activities. Ubiquitous and pervasive computing first identified the emerging challenges of studying technology used on-the-move and in widely varied contexts. With IoT, previously sporadic experiences are interconnected across time and space in numerous and complex ways. This increasing complexity has multiplied the challenges facing those who study human experience to inform design. This paper describes the results of a study that used a chatbot or 'Ethnobot' to gather ethnographic data, and considers the opportunities and challenges in collecting this data in the absence of a human ethnographer. This study involved 13 participants gathering information about their experiences at the Royal Highland Show. We demonstrate the effectiveness of the Ethnobot in this setting, discuss the benefits and drawbacks of chatbots as a tool for ethnographic data collection, and conclude with recommendations for the design of chatbots for this purpose.
Parasitism by Cuscuta pentagona Attenuates Host Plant Defenses against Insect Herbivores1

Considerable research has examined plant responses to concurrent attack by herbivores and pathogens, but the effects of attack by parasitic plants, another important class of plant-feeding organisms, on plant defenses against other enemies has not been explored. We investigated how attack by the parasitic plant Cuscuta pentagona impacted tomato (Solanum lycopersicum) defenses against the chewing insect beet armyworm (Spodoptera exigua; BAW). In response to insect feeding, C. pentagona-infested (parasitized) tomato plants produced only one-third of the antiherbivore phytohormone jasmonic acid (JA) produced by unparasitized plants. Similarly, parasitized tomato, in contrast to unparasitized plants, failed to emit herbivore-induced volatiles after 3 d of BAW feeding. Although parasitism impaired antiherbivore defenses, BAW growth was slower on parasitized tomato leaves. Vines of C. pentagona did not translocate JA from BAW-infested plants: amounts of JA in parasite vines grown on caterpillar-fed and control plants were similar. Parasitized plants generally contained more salicylic acid (SA), which can inhibit JA in some systems. Parasitized mutant (NahG) tomato plants deficient in SA produced more JA in response to insect feeding than parasitized wild-type plants, further suggesting cross talk between the SA and JA defense signaling pathways. However, JA induction by BAW was still reduced in parasitized compared to unparasitized NahG, implying that other factors must be involved. We found that parasitized plants were capable of producing induced volatiles when experimentally treated with JA, indicating that resource depletion by the parasite does not fully explain the observed attenuation of volatile response to herbivore feeding. Collectively, these findings show that parasitic plants can have important consequences for host plant defense against herbivores.
Wide Bandgap Devices in Electric Vehicle Converters: A Performance Survey

This paper introduces a unique quantified study about using low-losses fast-switching wide bandgap (WBG) devices, i.e., gallium nitride (GaN) and silicon carbide (SiC), over traditional Silicon (Si) devices in the switching of dc/dc converters, focusing on electric vehicles’ (EVs) machine drive and battery charger. A detailed model of the power train of a Nissan Leaf was developed in PSIM software, with WBG semiconductors’ capability. The model was simulated one time using GaN semiconductors and another time using SiC devices. Simulation results are quantified and a comparison between different semiconductors in terms of total losses and efficiency is presented. The developed PSIM model can also be extended to other EVs like Chevy Volt. A proof of concept prototype for a Nissan Leaf dc/dc converter was built in the laboratory and results were collected. Componentwise experimental results are presented and their correlation with simulation findings is demonstrated. In addition, experimental results of the overall power train test bench are found to be matched with the simulation results on a system level as well.