Miracle-dz/UniFAR-FTUs huggingface dataset:
Resolving Time Inconsistency in Financial Decision Problems With Non-Expectation Operator: From Internal Conflict to Internal Harmony by Strategy of Self-Coordination

When a stochastic decision problem is time inconsistent, the decision maker would always be troubled by his conflicting decisions “optimally” derived from his time-varying preferences at different time instants. The long-run self (LR) of the decision maker pursues the long-term optimality and thus would like to take the pre-committed strategy. On the other hand, the short-run selves (SRs) of the decision maker at different time instants lack foresight, bow to short-term temptations and would like to take the so-called time consistent strategy. As these two extreme strategies have been criticized for their incomplete viewpoints in dealing with time inconsistency, the emerging literature of self-control game models recognizes an importance to strike a balance between the LR’s and SRs’ interests. While most risk measures in financial decisions are of a non-expectation nature, the existing results of self-control game models are confined to situations where the decision maker’s preferences involve only expectation operators. We take a step forward to develop in this study an operable unified two-tier dual-self game model with commitment by punishment in continuous time setting, which can cope with general time inconsistent stochastic financial decision problems with both expectation and non-expectation operators in the objective function. By attaching to both the preferences of LR and SRs certain punishment terms which quantitatively evaluate the internal conflict among different selves, our game model can align the interests of the LR and SRs to any desired degree. The equilibrium strategy, termed strategy of self-coordination in this paper, achieves some degree of internal harmony among various selves. We demonstrate in the paper successful applications of our dual-self game model to two long standing challenges in the literature, the continuous-time investment and consumption problem with quasi-hyperbolic discounting and the continuous-time mean-variance portfolio selection problem.
Improving a Web-Based Tool to Support Older Adults to Stay Independent at Home: Qualitative Study

Background Older adults desire to stay independent at home for as long as possible. We developed an interactive website to inform older adults and caregivers about ways to achieve this. Objective This study aimed to perform an in-depth exploration among potential end users about how to improve the interactive website to better inform older adults and caregivers about ways to stay independent at home. Methods To complement the results of a quantitative survey on the usability and acceptability of the website before implementation, we conducted a qualitative descriptive study. Using multiple recruitment strategies, we recruited a purposeful sample of older adults (aged ≥65 years) and caregivers of older adults struggling to stay independent at home. We conducted face-to-face or telephonic interviews in either English or French. In addition, we collected sociodemographic characteristics, other characteristics of participants (eg, health, digital profile, and perception of retirement homes), and experiences with using the website (factors facilitating the use of the website, barriers to its use, and suggestions for improvement). Interviews were audio recorded, transcribed verbatim, and thematically analyzed by two researchers. Results We recruited 15 participants, including 5 older adults (mean age 75 years, SD 6) and 10 caregivers (mean age 57 years, SD 14). The mean interview time was 32 min (SD 14). Most older adults had either mobility or health problems or both, and many of them were receiving home care services (eg, blood pressure measurement and body care). Overall, participants found the website easy to navigate using a computer, reassuring, and useful for obtaining information. Barriers were related to navigation (eg, difficult to navigate with a cellphone), relevance (eg, no specific section for caregivers), realism (eg, some resources presented are not state funded), understandability (eg, the actors’ accents were difficult to understand), and accessibility (eg, not adapted for low digital literacy). Suggestions for improvement included a needs assessment section to direct users to the support appropriate to their needs, addition of information about moving into residential care, a section for caregivers, distinction between state-provided and private support services, simpler language, expansion of content to be relevant to all of Canada, and video subtitles for the hearing impaired. Conclusions Users provided a wealth of information about the needs of older adults who were facing a loss of autonomy and about what such a website could usefully provide. The request for less generic and more personalized information reflects the wide range of needs that electronic health innovations, such as our interactive website, need to address. After integrating the changes suggested, the new website—Support for Older Adults to Stay Independent at Home (SUSTAIN)—will be implemented and made available to better assist older adults and caregivers in staying independent at home.
Effect of Ten Insecticidal Plant Powders on Rice Weevil, Sitophilus oryzae L. and Grain Weight Loss in Stored Sorghum

Sorghum, Sorghum bicolor L. is called as ‘Camel of crops’ because of its hardiness and ability to withstand prolonged droughts. It is the fifth most important crop in the world after rice, wheat, corn and barley (Selva Rani et al., 2017). It accounts for an area of 8.9 million ha with production of 4.41 million tonnes in India and India is second largest producer of sorghum in the world (Pattanayak, 2016). Sorghum should be stored to meet home consumption as well as for sale.
Hatchling sex ratio and female mating status in the great reed warbler, Acrocephalus arundinaceus (Aves, Passeriformes): further evidence for offspring sex ratio manipulation

Abstract Offspring sex in birds is maternally determined, thus females are expected to vary brood sex ratio adaptively in response to various environmental and/or genetic conditions preferring one sex to the other sex. However, recent studies provide controversial evidence showing mixed support for adaptive sex manipulation theory. One problem may lie in the fact that only sex ratios at fledging have been used in many of these studies, ignoring post-hatching sex-biased mortality. To validate these results, some authors call for replication of previous researches. Here we examined hatchling sex ratio variation in relation to female mating status in a local population of facultatively polygynous great reed warblers Acrocephalus arundinaceus in Central Europe. In agreement with results of previous works, we found that monogamous and primary females had a higher proportion of sons in their broods than secondary females. These results provide further evidence that great reed warbler females manipulate the sex ratio of their offspring in response to their social status.
Bidirectional Partner Violence Among Homeless Young Adults

One of the most prevalent forms of violence in contemporary society is the victimization of intimate partners. Although it has been established that homeless young people experience high levels of victimization on the street, little is known about partner violence (PV) experiences among this group, especially bidirectional violence. As such, the purpose of this study is to examine the prevalence of PV and bidirectional violence and to investigate risk factors and outcomes of this form of violence using a sample of homeless young adults. Overall, 59% of the sample experienced bidirectional violence. Multivariate results reveal that sexual abuse and neglect are significant correlates of PV. In addition, being either a victim or perpetrator of PV is associated with more severe substance use and higher levels of posttraumatic stress disorder (PTSD). Finally, there is support for bidirectional violence among homeless young adults even after controlling for early histories of maltreatment.
Detection and characterization of two VLM binaries: LP 1033-31 and LP 877-72

Using the high-resolution near-infrared adaptive optics imaging from the NaCo instrument at the Very Large Telescope, we report the discovery of a new binary companion to the M-dwarf LP 1033-31 and also confirm the binarity of LP 877-72. We have characterized both the stellar systems and estimated the properties of their individual components. We have found that LP 1033-31 AB with the spectral type of M4.5+M4.5 has a projected separation of 6.7 ± 1.3 AU. Whereas with the spectral type of M1+M4, the projected separation of LP 877-72 AB is estimated to be 45.8 ± 0.3 AU. The binary companions of LP 1033-31 AB are found to have similar masses, radii, effective temperatures, and log g with the estimated values of 0.20 ± 0.04 $\rm {M}_{\odot }$, 0.22 ± 0.03 $\rm {R}_{\odot }$, and 3200 K, 5.06 ± 0.04. However, the primary of LP 877-72 AB is found to be twice as massive as the secondary with the derived mass of 0.520 ± 0.006 $\rm {M}_{\odot }$. The radius and log g for the primary of LP 877-72 AB are found to be 1.8 and 0.95 times that of the secondary component with the estimated values of 0.492 ± 0.011 $\rm {R}_{\odot }$ and 4.768 ± 0.005, respectively. With an effective temperature of 3750 ± 15 K, the primary of LP 877-72 AB is also estimated to be ∼400 K hotter than the secondary component. We have also estimated the orbital period of LP 1033-31 and LP 877-72 to be ∼28 and ∼349 yr, respectively. The binding energies for both systems are found to be >1043 erg, which signifies that both systems are stable.
Approximation Benefits of Policy Gradient Methods with Aggregated States

Folklore suggests that policy gradient can be more robust to misspecification than its relative, approximate policy iteration. This paper studies the case of state-aggregated representations, in which the state space is partitioned and either the policy or value function approximation is held constant over partitions. This paper shows a policy gradient method converges to a policy whose regret per period is bounded by ϵ, the largest difference between two elements of the state-action value function belonging to a common partition. With the same representation, both approximate policy iteration and approximate value iteration can produce policies whose per-period regret scales as [Formula: see text], where γ is a discount factor. Faced with inherent approximation error, methods that locally optimize the true decision objective can be far more robust. This paper was accepted by Hamid Nazerzadeh, data science. Supplemental Material: Data are available at https://doi.org/10.1287/mnsc.2023. 4788 .
Host Preference by Diachasmimorpha longicaudata (Hymneoptera: Braconidae) Reared on Larvae of Anastrepha fraterculus and Ceratitis capitata (Diptera: Tephritidae)

ABSTRACT The preferences of Diachasmimorpha longicaudata (Ashmead) for larvae of Anastrepha fraterculus (Wiedemann) and Ceratitis capitata (Wiedemann) were evaluated under laboratory conditions in no-choice and dual-choice tests, based on percent parasitism, proportion of emerged parasitoids, proportion of female offspring, and number of parasitoid female visits to and ovipositor probes on the artificial oviposition device as different measures of host preference. In no-choice tests D. longicaudata females did not demonstrate a significant preference between C. capitata and A. fraterculus larvae. Nevertheless, D. longicaudata females showed a strong preference for A. fraterculus larvae in dual-choice test. Although female biased parasitoid progeny resulted in all assays, significantly more D. longicaudata female offspring emerged from A. fraterculus pupae than from C. capitata pupae. Thus, this study confirmed that both C. capitata and A. fraterculus are appropriate host for rearing D. longicaudata, but also provided evidence that female parasitoid progeny yield can be substantially improved by using A. fraterculus larvae as the host instead of C. capitata larvae.
Nursing home staff networks and COVID-19

Significance Nursing homes account for 40% of US COVID-related fatalities as of August 31, highlighting the urgent need to reduce SARS-CoV-2 transmission routes in these facilities. Our large-scale analysis of smartphone location data reports half a million individuals entering a nursing home following the March 13 federal ban on visitors. With 5.1% of these individuals entering two or more facilities, a nursing home snapshot network emerges. More connections, likely arising from contractors and staff working at multiple facilities, are highly predictive of COVID-19 cases, whereas traditional regulatory quality metrics are unimportant in predicting outbreak size. With an estimated 49% of nursing home cases attributable to cross-facility staff movement, attention to highly connected nursing facilities is warranted. Nursing homes and other long-term care facilities account for a disproportionate share of COVID-19 cases and fatalities worldwide. Outbreaks in US nursing homes have persisted despite nationwide visitor restrictions beginning in mid-March. An early report issued by the Centers for Disease Control and Prevention identified staff members working in multiple nursing homes as a likely source of spread from the Life Care Center in Kirkland, WA, to other skilled nursing facilities. The full extent of staff connections between nursing homes—and the role these connections serve in spreading a highly contagious respiratory infection—is currently unknown given the lack of centralized data on cross-facility employment. We perform a large-scale analysis of nursing home connections via shared staff and contractors using device-level geolocation data from 50 million smartphones, and find that 5.1% of smartphone users who visited a nursing home for at least 1 h also visited another facility during our 11-wk study period—even after visitor restrictions were imposed. We construct network measures of connectedness and estimate that nursing homes, on average, share connections with 7.1 other facilities. Traditional federal regulatory metrics of nursing home quality are unimportant in predicting outbreaks, consistent with recent research. Controlling for demographic and other factors, a home’s staff network connections and its centrality within the greater network strongly predict COVID-19 cases.
Leveraging Bottom-Up and Top-Down Attention for Few-Shot Object Detection

Few-shot object detection aims at detecting objects with few annotated examples, which remains a challenging research problem yet to be explored. Recent studies have shown the effectiveness of self-learned top-down attention mechanisms in object detection and other vision tasks. The top-down attention, however, is less effective at improving the performance of few-shot detectors. Due to the insufficient training data, object detectors cannot effectively generate attention maps for few-shot examples. To improve the performance and interpretability of few-shot object detectors, we propose an attentive few-shot object detection network (AttFDNet) that takes the advantages of both top-down and bottom-up attention. Being task-agnostic, the bottom-up attention serves as a prior that helps detect and localize naturally salient objects. We further address specific challenges in few-shot object detection by introducing two novel loss terms and a hybrid few-shot learning strategy. Experimental results and visualization demonstrate the complementary nature of the two types of attention and their roles in few-shot object detection. Codes are available at this https URL.
PP-YOLO: An Effective and Efficient Implementation of Object Detector

Object detection is one of the most important areas in computer vision, which plays a key role in various practical scenarios. Due to limitation of hardware, it is often necessary to sacrifice accuracy to ensure the infer speed of the detector in practice. Therefore, the balance between effectiveness and efficiency of object detector must be considered. The goal of this paper is to implement an object detector with relatively balanced effectiveness and efficiency that can be directly applied in actual application scenarios, rather than propose a novel detection model. Considering that YOLOv3 has been widely used in practice, we develop a new object detector based on YOLOv3. We mainly try to combine various existing tricks that almost not increase the number of model parameters and FLOPs, to achieve the goal of improving the accuracy of detector as much as possible while ensuring that the speed is almost unchanged. Since all experiments in this paper are conducted based on PaddlePaddle, we call it PP-YOLO. By combining multiple tricks, PP-YOLO can achieve a better balance between effectiveness (45.2% mAP) and efficiency (72.9 FPS), surpassing the existing state-of-the-art detectors such as EfficientDet and YOLOv4.Source code is at this https URL.
A Veritable Zoology of Successive Phase Transitions in the Asymmetric q-Voter Model on Multiplex Networks

We analyze a nonlinear q-voter model with stochastic noise, interpreted in the social context as independence, on a duplex network. The size of the lobby q (i.e., the pressure group) is a crucial parameter that changes the behavior of the system. The q-voter model has been applied on multiplex networks, and it has been shown that the character of the phase transition depends on the number of levels in the multiplex network as well as on the value of q. The primary aim of this study is to examine phase transition character in the case when on each level of the network the lobby size is different, resulting in two parameters q1 and q2. In a system of a duplex clique (i.e., two fully overlapped complete graphs) we find evidence of successive phase transitions when a continuous phase transition is followed by a discontinuous one or two consecutive discontinuous phase transitions appear, depending on the parameter. When analyzing this system, we even encounter mixed-order (or hybrid) phase transition. The observation of successive phase transitions is a new quantity in binary state opinion formation models and we show that our analytical considerations are fully supported by Monte-Carlo simulations.
Deep Learning based, end-to-end metaphor detection in Greek language with Recurrent and Convolutional Neural Networks

This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state of the art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of the training tuples, the sentences and their labels. The outcome is a state of the art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.
Antioxidant response of a common herbivorous fish species (Sarpa salpa): Seasonal variation

Within the framework of a biosurveillance of marine species on Tunisian coasts, we studied the salema Sarpa salpa, a fish that is consumed by the people living in this region. There is a seasonal occurrence of hallucinogen effects observed when this fish is consumed by humans. The aim of this work was to determine the seasonal variation in the composition of this fish’s diet and to correlate this variation with the antioxidant activity found in its tissues. The salema that lives around the Island of Kerkennah is primarily a herbivorous fish during all seasons. We observed an increased expression of catalase (CAT) and glutathione peroxidase (GPx) in certain organs compared to the control fish, Diplodus annularis. There was a “season-depending” cumulative effect, appearing in the organs starting with the liver, followed by the brain, and finally the flesh. Moreover, it increases according to the size of the animal and thus to the amount of food it consumes. The hallucinogen effect that the consumption of salema has on humans is parallel to the seasonal variation in the epiphytes that are co-ingested by these fish with their food. A significant correlation (P < 0.01) was also observed between the total toxic dinoflagellates and the antioxidant response: CAT and GPx in liver, brain, and flesh for all seasons and all sizes together. En el marco de un muestreo biologico de las especies marinas en las costas de Tunez, se estudio la salema Sarpa salpa, un pescado que es consumido por los habitantes de esta region. Se ha observado un acontecimiento estacional de efectos alucinogenos en los seres humanos despues de consumir este pescado. El objetivo de este trabajo fue determinar la variacion estacional de la composicion de la dieta de S. salpa y correlacionar esta variacion con la actividad antioxidante observada en los tejidos. La salema que se encuentra alrededor de la isla de Kerkennah es principalmente un pez herbivoro durante todas las estaciones del ano. Se observo un incremento de la expresion de la catalasa (CAT) y la glutation peroxidasa (GPx) en ciertos organos en comparacion con el pez control, Diplodus annularis. Se encontro un efecto acumulativo dependiente de la estacion, que aparecio primero en el higado, despues en el cerebro y por ultimo en la carne. Ademas, se incrementa segun el tamano del animal y, por tanto, la cantidad de alimento que consume. El efecto alucinogeno que el consumo de la salema tiene en el ser humano se relaciona con la variacion estacional de las epifitas que son coingeridas por estos peces con su comida. Tambien se observo una correlacion significativa (P < 0.01) entre el total de dinoflagelados toxicos y la respuesta antioxidante: CAT y GPx en el higado, el cerebro y la carne para todas las estaciones y tallas en conjunto.
Quantum Differentially Private Sparse Regression Learning

The eligibility of various advanced quantum algorithms will be questioned if they can not guarantee privacy. To fill this knowledge gap, here we devise an efficient quantum differentially private (QDP) Lasso estimator to solve sparse regression tasks. Concretely, given <inline-formula> <tex-math notation="LaTeX">$N~d$ </tex-math></inline-formula>-dimensional data points with <inline-formula> <tex-math notation="LaTeX">$N\ll d$ </tex-math></inline-formula>, we first prove that the optimal classical and quantum non-private Lasso requires <inline-formula> <tex-math notation="LaTeX">$\Omega (N+d)$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$\Omega (\sqrt {N}+\sqrt {d})$ </tex-math></inline-formula> runtime, respectively. We next prove that the runtime cost of QDP Lasso is <italic>dimension independent</italic>, i.e., <inline-formula> <tex-math notation="LaTeX">$O(N^{5/2})$ </tex-math></inline-formula>, which implies that the QDP Lasso can be faster than both the optimal classical and quantum non-private Lasso. Last, we exhibit that the QDP Lasso attains a near-optimal utility bound <inline-formula> <tex-math notation="LaTeX">$\tilde {O}(N^{-2/3})$ </tex-math></inline-formula> with privacy guarantees and discuss the chance to realize it on near-term quantum chips with advantages.