Miracle-dz/UniFAR-FTUs huggingface dataset:
Bound to Lose: Physical Incapacitation Increases the Conceptualized Size of an Antagonist in Men

Because decision-making in situations of potential conflict hinges on assessing many features of the self and the foe, this process can be facilitated by summarizing diverse attributes in a single heuristic representation. Physical size and strength are evolutionarily ancient determinants of victory in conflict, and their relevance is reinforced during development. Accordingly, size and muscularity constitute ready dimensions for a summary representation of relative formidability, a perspective paralleled by the notion that social power is represented using envisioned relative size. Physical incapacitation constitutes a significant tactical disadvantage, hence temporary incapacitation should increase the envisioned size and strength of an antagonist. In Study 1, being bound to a chair increased men’s estimates of the size of an angry man and decreased estimates of their own height. Study 2 conceptually replicated these effects: among men for whom standing on a balance board was challenging, the attendant experience of postural instability increased estimates of an angry man’s size and muscularity, with similar patterns occurring at a reduced level among all but those whose equilibrium was apparently unaffected by this task.
Functional Synchronization of Biological Rhythms in a Tritrophic System

In a tritrophic system formed by a plant, an herbivore and a natural enemy, each component has its own biological rhythm. However, the rhythm correlations among the three levels and the underlying mechanisms in any tritrophic system are largely unknown. Here, we report that the rhythms exhibited bidirectional correlations in a model tritrophic system involving a lima bean, a pea leafminer and a parasitoid. From the bottom-up perspective, the rhythm was initiated from herbivore feeding, which triggered the rhythms of volatile emissions; then the rhythmic pattern of parasitoid activities was affected, and these rhythms were synchronized by a light switch signal. Increased volatile concentration can enhance the intensity of parasitoid locomotion and oviposition only under light. From the top-down perspective, naive and oviposition-experienced parasitoids were able to utilize the different volatile rhythm information from the damaged plant to locate host leafminers respectively. Our results indicated that the three interacting organisms in this system can achieve rhythmic functional synchronization under a natural light-dark photoperiod, but not under constant light or darkness. These findings provide new insight into the rhythm synchronization of three key players that contribute to the utilization of light and chemical signals, and our results may be used as potential approaches for manipulating natural enemies.
Transforming growth factor‐β1 localization in normal and psoriatic epidermal keratinocytes in situ

Transforming growth factor‐β1 (TGFβ1) is a potent inhibitor of epithelial cell proliferation and its effects on growth and differentiation have been extensively characterized in cultured keratinocytes. We used two TGFβ1‐specific polyclonal antibodies (anti‐LC and anti‐CC) to determine the presence of TGFβ1 peptide in keratinocytes in sections of normal human skin in situ and in both plaque and nonplaque skin from individuals with psoriasis. In contrast to the differentiation phenotype expressed by keratinocytes in normal epidermis, keratinocytes in the psoriatic plaque exhibit a hyperproliferative/regenerative differentiation phenotype. Anti‐TGFβ1 staining was observed primarily in the epidermis. Anti‐LC TGFβ1 antibody stained nonproliferating, differentiated suprabasal keratinocytes intracellularly in normal skin but did not stain psoriatic plaques from five of seven patients. In contrast, anti‐CC TGFβ1 antibody stained suprabasal keratinocytes extracellularly in psoriatic plaques, but did not stain normal skin. Both anti‐LC and anti‐CC stained suprabasal keratinocytes intracellularly in nonplaque psoriatic skin. Thus, the conformation or structure of TGFβ1 and its localization vary in keratinocytes with distinct differentiation phenotypes suggesting that TGFβ1 is a potential modulator of keratinocyte differentiation in vivo. Selective association of TGFβ1 with nonproliferating keratinocytes in the suprabasal layers of the epidermis and its exclusion from the proliferating keratinocytes in the basal layer suggest that it may be a Physiological regulator of keratinocyte proliferation. In addition, the intracellular localization of TGFβ1 peptide in both normal and psoriatic keratinocytes suggests that it is constitutively synthesized by epidermal keratinocytes in vivo.
Single Sample Fictitious Play

This paper is concerned with distributed learning and optimization in large-scale settings. The well-known fictitious play (FP) algorithm has been shown to achieve Nash equilibrium learning in certain classes of multiagent games. However, FP can be computationally difficult to implement when the number of players is large. Sampled FP (SFP) is a variant of FP that mitigates the computational difficulties arising in FP by using a Monte Carlo (i.e., sampling based) approach. Despite its computational advantages, a shortcoming of SFP is that the number of samples that must be drawn at each iteration grows without bound as the algorithm progresses. In this paper, we propose single sample FP (SSFP)—A variant of SFP in which only one sample needs to be drawn in each round of the algorithm. Convergence of SSFP to the set of Nash equilibria is proven. Simulation results show the performance of SSFP is comparable to that of SFP, despite drawing far fewer samples.
The impact of EV/PHEV chargers on residential loads - A case study

Electric and plug-in hybrid electric vehicles typically utilize multi level chargers which are powered by solid-state converters. These converters increase harmonic levels which can potentially impact adjacent residential loads as well as the local distribution grid. Such impacts will become more prevalent in the near future as electric vehicle adoption increases. This paper investigates the harmonic impacts generated by an electric vehicle charger on residential distribution systems within a controlled lab environment. The outcomes from this research will be utilized to identify mitigation plans in support of utilities' smart grid implementation programs.
Treatment-as-Prevention in AIDS Control: Why Communication Still Matters

Treatment-as-prevention is a term used to describe an HIV prevention method that uses antiretroviral treatment to minimize the chance of HIV transmission, with the idea that treatment can decrease the viral load of those infected to a level where transmission risk is minimal. However, for treatment-as-prevention to be a success, individuals must get tested, know their status, seek care, and adhere to their antiretroviral regimen. Communication plays a role in each of these steps, as communication can be used to create demand for health-seeking behavior and as a means to increase quality and support on the supply side, at the clinic and community level. From the demand side, communication has played a role in convincing people to get tested and obtain their results, in ensuring treatment access, linking those infected to care, and addressing stigmatizing attitudes that may prevent individuals from taking these actions. On the supply side, communication has been shown to mobilize community care and support and increase the quality of patient-provider interaction, which in turn can improve adherence. Finally, communication has played an integral role in structural issues related to treatment-as-prevention, including the assurance of adequate supplies, including HIV testing kits, anti-retrovirals, and condoms.
Evolution of the F0F1 ATP Synthase Complex in Light of the Patchy Distribution of Different Bioenergetic Pathways across Prokaryotes

Bacteria and archaea are characterized by an amazing metabolic diversity, which allows them to persist in diverse and often extreme habitats. Apart from oxygenic photosynthesis and oxidative phosphorylation, well-studied processes from chloroplasts and mitochondria of plants and animals, prokaryotes utilize various chemo- or lithotrophic modes, such as anoxygenic photosynthesis, iron oxidation and reduction, sulfate reduction, and methanogenesis. Most bioenergetic pathways have a similar general structure, with an electron transport chain composed of protein complexes acting as electron donors and acceptors, as well as a central cytochrome complex, mobile electron carriers, and an ATP synthase. While each pathway has been studied in considerable detail in isolation, not much is known about their relative evolutionary relationships. Wanting to address how this metabolic diversity evolved, we mapped the distribution of nine bioenergetic modes on a phylogenetic tree based on 16S rRNA sequences from 272 species representing the full diversity of prokaryotic lineages. This highlights the patchy distribution of many pathways across different lineages, and suggests either up to 26 independent origins or 17 horizontal gene transfer events. Next, we used comparative genomics and phylogenetic analysis of all subunits of the F0F1 ATP synthase, common to most bacterial lineages regardless of their bioenergetic mode. Our results indicate an ancient origin of this protein complex, and no clustering based on bioenergetic mode, which suggests that no special modifications are needed for the ATP synthase to work with different electron transport chains. Moreover, examination of the ATP synthase genetic locus indicates various gene rearrangements in the different bacterial lineages, ancient duplications of atpI and of the beta subunit of the F0 subcomplex, as well as more recent stochastic lineage-specific and species-specific duplications of all subunits. We discuss the implications of the overall pattern of conservation and flexibility of the F0F1 ATP synthase genetic locus.
Evaluation of performance and scalability of Mininet in scenarios with large data centers

Due to the increased demand for internet services, the challenges that large data centers must handle are bigger. Therefore, in recent years the development of networks defined by software (SDN) has caught the attention of the scientific community, mainly because of the flexibility it presents in its model of centralized management, which facilitates the development of solutions according to demand of the network and / or users. Mininet is one of the most commonly tools used for the study of SDNs, as it allows to recreate data networks that can support various topologies and protocols. Nevertheless, like any other emulation software Mininet has limitations due to the restrictions of the hardware/software platform where it runs, which prevents it to scale to large networks. We present a characterization of the performance and scalability of Mininet via an experimental analysis. For this purpose, we used a typical topology for large data centers. The results let us conclude that, under some restrictions, Mininet gives results in accord with the theoretical expectation. In other cases, the emulation platform exhibits strong dependence on the performance of underlying hardware/software system as well as on the operation mode of the SDN controller used in the network.
The Effect of Narrative Reminiscence on Happiness of Elderly Women

Background: Happiness has a considerable impact on elderly quality of life. Reminiscence therapy can be an effective intervention in increasing the positive emotions among elderly. Objectives: This study was performed to investigate the effect of reminiscence therapy on Iranian elderly women’s happiness. Patients and Methods: This randomized clinical trial conducted on 32 elderly women (census sampling) attending the jahandidegan daycare elderly center IN Gorgan city, Iran, in 2013. Happiness scores of 4 phases were measured: before, the third session, the sixth session and one month after the intervention. Three instruments were used in this study including a demographic questionnaire, the mini mental state examination test, and Oxford happiness questionnaire. The intervention group participated in six sessions of narrative group reminiscence that were held in three consecutive weeks, two sessions per week. The control group was also participated in six sessions of group discussions that were held in three consecutive weeks, two sessions per week. Data analysis was performed the chi-square, independent t-test, Paired t-test. Results: From a total of 32 elderly women, 29 cases completed the study. No significant differences were found between the two groups in terms of demographic characteristics. The mean happiness scores before the intervention between the two groups were not significantly different (P = 0.824). Comparison of the mean happiness scores of the intervention group in the four measurement times revealed a significant difference only after the third and sixth sessions (P = 0.03), and no significant difference was found between the mean happiness scores of the control group in the four measurement times. Conclusions: The elderly participating in the matched group sessions can be effective in increasing positive emotions.
Artificial Placenta - Lung Assist Devices for Term and Preterm Newborns with Respiratory Failure

Respiratory insufficiency is a major cause of neonatal mortality and long-term morbidity, especially in very low birth weight infants. Today, non-invasive and mechanical ventilation are commonly accepted procedures to provide respiratory support to newborns, but they can reach their limit of efficacy. To overcome this technological plateau and further reduce mortality rates, the technology of an “artificial placenta”, which is a pumpless lung assist device connected to the umbilical vessels, would serve to expand the therapeutic spectrum when mechanical ventilation becomes inadequate to treat neonates with severe respiratory insufficiency. The first attempts to create such an artificial placenta took place more than 60 years ago. However, there has been a recent renaissance of this concept, including developments of its major components like the oxygenator, vascular access via umbilical vessels, flow control, as well as methods to achieve hemocompatibility in extracorporeal circuits. This paper gives a review of past and current development, animal experiments and human case studies of artificial placenta technology.
Extended Crossover Model for Human-Control of Fractional Order Plants

A data-driven generalization of the crossover model is proposed, characterizing the human control of systems with both integer and fractional-order plant dynamics. The model is developed and validated using data obtained from human subjects operating in compensatory and pursuit tracking tasks. From the model, it is inferred that humans possess a limited but consistent capability to compensate for fractional-order plant dynamics. Further, a review of potential sources of fractionality within such man–machine systems suggests that visual perception, based on visual cues that contain memory, and muscular dynamics are likely sources of fractional-order dynamics within humans themselves. Accordingly, a possible mechanism for fractional-order compensation, operating between visual and muscular sub-systems, is proposed. Deeper analysis of the data shows that human response is more highly correlated to fractional-order representations of visual cues, rather than directly to objective engineering variables, as is commonly proposed in human control models in the literature. These results are expected to underpin future design developments in human-in-the-loop cyber-physical systems, for example, in semi-autonomous highway driving.
End to end very deep person re-identification

Convolutional Neural Networks (CNNs) are responsible for major breakthroughs in object recognition in still images. This work presents an end to end very deep architecture with small convolutional kernel size, small convolutional strides and very deep network architecture for person re-identification in video streams. To achieve such system several good practices for the training were tested, namely: (i) training from scratch, (ii) pre-training last layer, (iii) small learning rates, (iv) data augmentation techniques, (v) high dropout ratio. The key contribution of this paper is a trainable, end-to-end deep network approach that allows for effective re-identification in real time of people in multiple-stream video from various sources (indoor and outdoor). Experimental evaluation was conducted on a real-world publicly available dataset showing the benefits of this approach.
Online Diarization of Streaming Audio-Visual Data for Smart Environments

For an environment to be perceived as being smart, contextual information has to be gathered to adapt the system's behavior and its interface towards the user. Being a rich source of context information speech can be acquired unobtrusively by microphone arrays and then processed to extract information about the user and his environment. In this paper, a system for joint temporal segmentation, speaker localization, and identification is presented, which is supported by face identification from video data obtained from a steerable camera. Special attention is paid to latency aspects and online processing capabilities, as they are important for the application under investigation, namely ambient communication. It describes the vision of terminal-less, session-less and multi-modal telecommunication with remote partners, where the user can move freely within his home while the communication follows him. The speaker diarization serves as a context source, which has been integrated in a service-oriented middleware architecture and provided to the application to select the most appropriate I/O device and to steer the camera towards the speaker during ambient communication.
Large-scale controlled synthesis of silica nanotubes using zinc oxide nanowires as templates

We report on the controlled synthesis of silica nanotubes on a large scale using ZnO nanowires as templates. The ZnO nanowires are first coated with a uniform silica layer by a sol–gel method. Then silica nanotubes are obtained after removal of ZnO nanowires in diluted hydrochloric acid solution. The thickness of the outer walls is tuned from ∼5 to ∼30 nm and the inner diameter is completely dependent on the size of the ZnO nanowires. Moreover, three-dimensional nanotubes such as tetrapod-like silica nanotubes are also synthesized through the same approach. Silica nanotubes with various thicknesses of outer walls and with special morphologies are expected to have potential applications in designing and fabricating novel nanodevices.
Deep Learning Applied to Image and Text Matching

The ability to describe images with natural language sentences is the hallmark for image and language understanding. Such a system has wide ranging applications such as annotating images and using natural sentences to search for images.In this project we focus on the task of bidirectional image retrieval: such asystem is capable of retrieving an image based on a sentence (image search) andretrieve sentence based on an image query (image annotation). We present asystem based on a global ranking objective function which uses a combinationof convolutional neural networks (CNN) and multi layer perceptrons (MLP). It takes a pair of image and sentence and processes them in different channels,finally embedding it into a common multimodal vector space. These embeddingsencode abstract semantic information about the two inputs and can be comparedusing traditional information retrieval approaches. For each such pair, the modelreturns a score which is interpretted as a similarity metric. If this score is high,the image and sentence are likely to convey similar meaning, and if the score is low then they are likely not to. The visual input is modeled via deep convolutional neural network. On theother hand we explore three models for the textual module. The first one isbag of words with an MLP. The second one uses n-grams (bigram, trigrams,and a combination of trigram & skip-grams) with an MLP. The third is morespecialized deep network specific for modeling variable length sequences (SSE). We report comparable performance to recent work in the field, even though ouroverall model is simpler. We also show that the training time choice of how wecan generate our negative samples has a significant impact on performance, and can be used to specialize the bi-directional system in one particular task.
Construction of the Automated Data Processing and Delayed-Mode Quality Control System for Profiling Floats

An automated data processing and quality management system for profiling floats of the ARGO project has been constructed. The system automatically process profiling float data after about 20 hours from its descent, and store data in the database system. The float data is publicized through World Wide Web. For the quality control of float data, we prepared historical database such as WOA98 and HydroBase, and gather neighboring ocean data in geographical/time on GTS via NEAR-GOOS Regional Real-Time Data Base. The system enable us to quality management using such as overlay plot of the float data and historical/neighboring data and so on.
Identification of Novel Oncogenes and Tumor Suppressors in Hepatocellular Carcinoma

Identification of novel oncogenes and tumor suppressors in hepatocellular carcinoma (HCC) is challenging, both because of the tumor complexity and the difficulty in integrating the very large amount of data provided by different approaches. The authors consider it very important to identify new pathways of carcinogenesis and to understand the mechanisms underlying their alteration in tumors to design personalized treatments for HCC. In this review, the main global genomic approaches are considered in detail. The authors present a catalog of the most important oncogenes and tumor suppressor genes that have been found to be mutated in HCC and hepatocellular adenoma. They also review the results provided by transcriptome and miRNA profiling, in terms of molecular tumor classification. The authors anticipate that high-throughput sequencing will considerably refine the description of the genetic alterations in HCC. They also predict that systems biology, the recently developed interdisciplinary research field, will be very important to integrate the colossal amounts of data generated by the new technologies and to identify useful clinical applications.
Statistical analysis of stochastic multi-robot boundary coverage

We present a novel analytical approach to computing the population and geometric parameters of a multi-robot system that will provably produce specified boundary coverage statistics. We consider scenarios in which robots with no global position information, communication, or prior environmental data have arrived at uniformly random locations along a simple closed or open boundary. This type of scenario can arise in a variety of multi-robot tasks, including surveillance, collective transport, disaster response, and therapeutic and imaging applications in nanomedicine. We derive the probability that a given point robot configuration is saturated, meaning that all pairs of adjacent robots are no farther apart than a specified distance. This derivation relies on a geometric interpretation of the saturation probability and an application of the Inclusion-Exclusion Principle, and it is easily extended to finite-sized robots. In the process, we obtain formulas for (a) an integral that is in general computationally expensive to compute directly, and (b) the volume of the intersection of a regular simplex with a hypercube. In addition, we use results from order statistics to compute the probability distributions of the robot positions along the boundary and the distances between adjacent robots. We validate our derivations of these probability distributions and the saturation probability using Monte Carlo simulations of scenarios with both point robots and finite-sized robots.