Miracle-dz/UniFAR-FTUs huggingface dataset:
Conditions for the clean slate effect after success or failure

ABSTRACT The act of physically cleaning one’s hands may reduce the impact of past experiences, termed clean-slate effect. Cleaning was found to affect negative, neutral, and mildly positive states. We extend this influence to success, a self-serving state. We manipulated success vs. failure and measured changes in optimism (Experiment 1) or self-esteem (Experiment 2). Moreover, we examined boundary conditions for the clean-slate effect. Experiment 1 indicates that the influence of performance on optimism diminishes if participants knew (compared to did not know) they were cleaning their hands. Experiment 2 indicates that the influence of performance on self-esteem diminishes if participants cleaned themselves (compared to an object). These results suggest that the clean-slate effect requires both awareness and self-reference of the cleaning act. Thus, the clean-slate effect seems to depend on both conscious inferences and automatic processes. A meta-analysis across the experiments confirms a moderate-sized clean-slate effect.
Preventing Colluding Identity Clone Attacks in Online Social Networks

Nowadays, Online Social Networks (OSNs) has become one of the most common ways among people to facilitate communication. This has made it a target for attackers to steal information from influential users and has brought new forms of customized attacks for OSNs. Attackers take advantage of the user's trustworthiness when using OSN. This exploitation leads to attacks with a combination of both classical and modern threats. Specifically, colluding attackers have been taken advantage of many OSNs by creating fake profiles of friends of the target in the same OSN or others. Colluders impersonate their victims and ask friend requests to the target in the aim to infiltrate her private circle to steal information. These types of attacks are difficult to detect in OSNs because multiple malicious users may have a similar purpose to gain information from their targeted user. The purpose of this paper is to overcome this type of attack by addressing the problem of matching user profiles across multiple OSNs. Then, we will extract both features and text from a user's profile and build a classifier based on supervised learning techniques. Simulation and experimental results are provided to validate the accuracy of our findings.
ATRIUM: Runtime attestation resilient under memory attacks

Remote attestation is an important security service that allows a trusted party (verifier) to verify the integrity of a software running on a remote and potentially compromised device (prover). The security of existing remote attestation schemes relies on the assumption that attacks are software-only and that the prover's code cannot be modified at runtime. However, in practice, these schemes can be bypassed in a stronger and more realistic adversary model that is hereby capable of controlling and modifying code memory to attest benign code but execute malicious code instead — leaving the underlying system vulnerable to Time of Check Time of Use (TOCTOU) attacks. In this work, we first demonstrate TOCTOU attacks on recently proposed attestation schemes by exploiting physical access to prover's memory. Then we present the design and proof-of-concept implementation of ATRIUM, a runtime remote attestation system that securely attests both the code's binary and its execution behavior under memory attacks. ATRIUM provides resilience against both software- and hardware-based TOCTOU attacks, while incurring minimal area and performance overhead.
Behavioral Responses of Pityophthorus juglandis (Coleoptera: Curculionidae: Scolytinae) to Volatiles of Black Walnut and Geosmithia morbida (Ascomycota: Hypocreales: Bionectriaceae), the Causal Agent of Thousand Cankers Disease

Abstract Thousand cankers disease (TCD) is a pest complex formed by the association of the walnut twig beetle (WTB), Pityophthorus juglandis Blackman (Coleoptera: Curculionidae: Scolytinae), with the fungal pathogen Geosmithia morbida Kolařík, Freeland, Utley and Tisserat (Ascomycota: Hypocreales: Bionectriaceae). Current monitoring and detection efforts for WTB rely on a pheromone lure that is effective over a limited distance while plant- and fungal-derived volatiles that may facilitate host location remain poorly understood. In this study, we test the hypothesis that adult beetles are attracted to volatiles of black walnut, Juglans nigra L. (Juglandaceae), and the pathogen, G. morbida. We measured the response of beetles to head-space volatiles collected from leaves and stems of 12 genotypes of black walnut and found genotypic variation in the attractiveness of host trees to adult WTB. Volatile profiles of the most attractive genotypes contained more α-pinene and β-pinene, and adult beetles were attracted to both of these compounds in olfactometer bioassays. In bioassays, we also demonstrated that adult WTB are attracted to volatiles of G. morbida. These findings suggest that, in addition to the aggregation pheromone, dispersing WTB potentially use host plant and fungal volatiles to locate suitable larval hosts. Finally, we conducted a field experiment to determine the extent to which ethanol, a common attractant for bark beetles, and limonene, a known bark beetle repellent, influence the behavior of adult WTB to pheromone-baited traps. Although ethanol did not increase trap capture, WTB were repelled by limonene, suggesting that this compound could be used to manipulate and manage WTB populations.
Temporal and spatial influences incur reconfiguration of Arctic heathland soil bacterial community structure.

Microbial responses to Arctic climate change could radically alter the stability of major stores of soil carbon. However, the sensitivity of plot-scale experiments simulating climate change effects on Arctic heathland soils to potential confounding effects of spatial and temporal changes in soil microbial communities is unknown. Here, the variation in heathland soil bacterial communities at two survey sites in Sweden between spring and summer 2013 and at scales between 0-1 m and, 1-100 m and between sites (> 100 m) were investigated in parallel using 16S rRNA gene T-RFLP and amplicon sequencing. T-RFLP did not reveal spatial structuring of communities at scales < 100 m in any site or season. However, temporal changes were striking. Amplicon sequencing corroborated shifts from r- to K-selected taxon-dominated communities, influencing in silico predictions of functional potential. Network analyses reveal temporal keystone taxa, with a spring betaproteobacterial sub-network centred upon a Burkholderia operational taxonomic unit (OTU) and a reconfiguration to a summer sub-network centred upon an alphaproteobacterial OTU. Although spatial structuring effects may not confound comparison between plot-scale treatments, temporal change is a significant influence. Moreover, the prominence of two temporally exclusive keystone taxa suggests that the stability of Arctic heathland soil bacterial communities could be disproportionally influenced by seasonal perturbations affecting individual taxa.
Chronotype and response to training during the polar night: a pilot study

ABSTRACT Background: An individual’s chronotype influences his or her physiological rhythms. Some studies have looked at the effect of time of day on the responses to exercise, but studies on the effect of long-term training are lacking. Objective: To report the effects of an 8-week training period during the polar night in non-athletes of different chronotypes living at 70°N. Design: In all, 10 morning (M), 10 neither (N) and 10 evening (E) types were recruited, and their aerobic capacity (VO2max), strength, flexibility and balance before and after the training period were tested. Results: 3 E-types, 5 N-types and 6 M-types completed the protocol. An increase in VO2max and strength was observed for the whole group. The best negative correlation (r=–0.5287) was found between the Morningness–Eveningness Questionnaire (MEQ) score and the increase in VO2max, and the best positive correlation (r=0.4395) was found between MEQ and the increase in strength. Changes in balance and flexibility did not show any clear trends. Conclusion: In an environment with no outdoor daylight, it seems that the response to 8 weeks of aerobic training is larger in the E- than in the M-types, although the M-types showed a larger improvement in strength.
Comparison of laparoscopic gastropexy performed via intracorporeal suturing with knotless unidirectional barbed suture using a needle driver versus a roticulated endoscopic suturing device: 30 cases

OBJECTIVE To compare two suturing techniques for prophylactic laparoscopic gastropexy in healthy dogs. STUDY DESIGN Retrospective case series. ANIMALS Thirty healthy client-owned dogs from breeds predisposed to gastric dilation volvulus. METHODS Medical records of dogs presented for prophylactic laparoscopic gastropexy performed with knotless unidirectional barbed suture were reviewed. Dogs were grouped based on the device used for suturing, consisting of an endoscopic needle driver (END) vs an endoscopic suturing device (ESD). Signalment, weight, surgery time, number of suture bites per side of gastropexy, and intraoperative complications were compared between groups. RESULTS The END group consisted of 10 dogs, with a median age of 1.09 years (range 0.5-2.67), weight of 41.5 kg (range 25-66), surgical time of 49.5 minutes (range 35-77), and a median of 5 suture bites per side (range 4-6). The ESD group included 20 dogs, with a median age of 1.75 years (range 0.6-8.75, P = .0944), weight was 37.5 kg (range 20-62, P = .5823), surgical time of 55 minutes (range 30-76, P = .808), and a median of 6 suture bites for the first side (range 4-7, P = .072) and 7 for the second side (range 4-8, P = .003). No major complications and no conversion to open celiotomy occured in either group. Minor complications occurred in 3 dogs in the ESD group, all related to device dysfunction and suture breakage. CONCLUSION Laparoscopic gastropexy may be performed effectively with either of these suturing techniques.
DeepSpotCloud: Leveraging Cross-Region GPU Spot Instances for Deep Learning

Cloud computing resources that are equipped with GPU devices are widely used for applications that require extensive parallelism, such as deep learning. When the demand of cloud computing instance is low, the surplus of resources is provided at a lower price in the form of spot instance by AWS EC2. This paper proposes DeepSpotCloud that utilizes GPU-equipped spot instances to run deep learning tasks in a cost efficient and fault-tolerant way. Thorough analysis about spot instance price history logs reveals that GPU spot instances show more dynamic price change pattern than other general types of cloud computing resources. To deal with the price dynamicity of the GPU spot instance, DeepSpotCloud utilizes instances in different regions across continents as a single resource pool. This paper also proposes a task migration heuristic by utilizing a checkpointing mechanism of existing deep learning analysis platform to conduct fast task migration when a running spot instance is interrupted. Extensive experiments using real AWS services prove that the proposed task migration method is effective even in a WAN environment with limited network bandwidth. Comprehensive simulations by replaying AWS EC2 price history logs reveal that DeepSpotCloud can achieve 13% more cost gain than a state-of-the-art interrupt-driven scheduling policy. The prototype of DeepSpotCloud is implemented using various cloud computing services provided by AWS to serve real deep learning tasks.
Improving Geographic Equity in Kidney Transplantation Using Alternative Kidney Sharing and Optimization Modeling

The national demand for kidney transplantation far outweighs the supply of kidney organs. Currently, a patient's ability to receive a kidney transplant varies depending on where he or she seeks transplantation. This reality is in direct conflict with a federal mandate from the Department of Health and Human Services. We analyze current kidney allocation and develop an alternative kidney sharing strategy using a multiperiod linear optimization model, KSHARE. KSHARE aims to improve geographic equity in kidney transplantation while also respecting transplant system constraints and priorities. KSHARE is tested against actual 2000–2009 kidney allocation using Organ Procurement and Transplant Network data. Geographic equity is represented by minimizing the range in kidney transplant rates around local areas of the country. In 2009, less than 25% of standard criteria donor kidneys were allocated beyond the local area of procurement, and Donor Service Area kidney transplantation rates varied from 3.0% to 30.0%, for an overall range of 27.0%. Given optimal sharing of kidneys within 600 miles of procurement for 2000–2009, kidney transplant rates vary from 5.0% to 12.5% around the country for an overall kidney transplant range of 7.5%. Nationally sharing kidneys optimally between local areas only further decreases the transplant rate range by 1.7%. Enhancing the practice of sharing kidneys by the KSHARE model may increase geographic equity in kidney transplantation.
Inhibition of glycogen phosphorylase stimulates ventromedial hypothalamic nucleus AMP‐activated protein kinase

The glucose polymer glycogen is a vital fuel reserve in the brain. The mediobasal hypothalamic energy sensor AMP‐activated protein kinase (AMPK) maintains glucostasis via neurotransmitter mechanisms that suppress [γ‐aminobutyric acid; GABA] or stimulate [nitric oxide; steroidogenic factor‐1 (SF1)] counter‐regulatory outflow. This study investigated whether glycogen‐derived fuel supply is a critical screened variable in ventromedial hypothalamic nucleus (VMN) monitoring of neuro‐metabolic stability during glucostasis and/or insulin (I)‐induced hypoglycemia. Adult male rats were pretreated by intra‐VMN infusion of the glycogen phosphorylase inhibitor 1,4‐dideoxy‐1,4‐imino‐D‐arabinitol (DAB) before sc vehicle or I injection. Western blot analyses of micropunch‐dissected VMN tissue from euglycemic animals showed DAB augmentation of phosphoAMPK (pAMPK), neuronal nitric oxide synthase (nNOS), and SF‐1, but not glutamate decarboxylase65/67 (GAD) protein. Combinatory DAB/I treatment did not further enhance AMPK activity but significantly amplified nNOS expression relative to DAB alone. Hypoglycemic stimulation of corticosterone, but not glucagon release was prevented by DAB. Results imply that glycogen‐derived substrate fuel provision represses VMN AMPK activity and neurotransmitter signals of metabolic deficiency. Progressive augmentation of nNOS protein by DAB/I versus DAB/V intimates that “fuel‐inhibited” nitrergic neurons may exhibit increasing sensitivity to disrupted glycogen breakdown during glucoprivation versus glucostasis. nNOS and GAD reactivity to DAB/I, but not I implies that acute glycogen utilization during hypoglycemia may be sufficiently robust to avert effects on local metabolic sensory signaling. DAB/I upregulation of GAD alongside prevention of hypercorticosteronemia suggests that indicators of metabolic sufficiency may occur secondary to local compensatory adaptations to severe restriction of glucose‐derived energy.
SES-LSH: Shuffle-Efficient Locality Sensitive Hashing for Distributed Similarity Search

Locality Sensitive Hashing (LSH) is a widely used similarity search technique for many web services, such as content-based retrieval services for images and videos. Due to its popularity, much research effort has been devoted to improving the search quality, and the indexing and query performance of LSH. However, most existing variants of LSH can only run on single node, which limits their applicability to large-scale data. In this paper, we present a Shuffle-Efficient Similarity Search scheme based on LSH, which can be efficiently executed in distributed environments, to serve a massive amount of data. In SES-LSH, a shuffle efficient indexing scheme is proposed to reduce the data shuffle when constructing hash tables, and a location-aware querying scheme is proposed to improve the query performance. We have implemented a prototype of SES-LSH based on Spark, and several optimizations have been utilized to improve the fine-grained hash table operations of distributed LSH. Extensive experiments using large-scale real-world datasets show that SES-LSH is remarkably more efficient than existing methods.
A Damage Simulation Technique of the Full Rock Creep Process Considering Accelerated Creep

On the basis of the mechanism of rock creep,the rock creep process was regarded as the superposition of linear and nonlinear rock creep process according to its phase characteristic.An elastic-plasticity damage cell model,which can describe the nonlinear or accelerated rock creep process,was developed by introducing the damage theory and the law of damage proposed by Kachanov.Connected with Kelvin cell model,which can preferably simulate the linear or the decelerated rock creep process,a rock creep model reflecting the features of the full rock creep process was obtained.The accelerated rock creep process was established and its simple and feasible parameter determination method was put forward.A new technique simulating the full rock creep process was developed,which can simulate the rock deformation process from decelerated to accelerated creep,and its parameters are few and easy to be determined.Finally,it shows that the model or technique proposed is reasonable and feasible after a comparison between the model and the experimental curves.
A Preventive Auto-Parallelization Approach for Elastic Stream Processing

Nowadays, more and more sources (connected devices, social networks, etc.) emit real-time data with fluctuating rates over time. Existing distributed stream processing engines (SPE) have to resolve a difficult problem: deliver results satisfying end-users in terms of quality and latency without over-consuming resources. This paper focuses on parallelization of operators to adapt their throughput to their input rate. We suggest an approach which prevents operator congestion in order to limit degradation of results quality. This approach relies on an automatic and dynamic adaptation of resource consumption for each continuous query. This solution takes advantage of i) a metric estimating the activity level of operators in the near future ii) the AUTOSCALE approach which evaluates the need to modify parallelism degrees at local and global scope iii) an integration into the Apache Storm solution. We show performance tests comparing our approach to the native solution of this SPE.
Preliminary research on behaviors of recycled concrete - filled steel stub columns

Experiments on eight recycled concrete - filled steel stub columns as well as two concrete -filled steel stub columns subjected to axial loading were carried out. The relationships of load - deformation curves and loading capacity between recycled concrete - filled steel tubes and concrete - filled steel tubes were compared. The load - deformation curves calculated by numerical method indicate good agreement with experimental results. By using current design codes to calculate the loading capacity of recycled concrete - filled steel tubes, the applicability of different codes in calculating loading capacity of recvcled concrete - filled steel tubes were discussed.
The contribution of toll‐like receptor signaling to the development of liver fibrosis and cancer in hepatocyte‐specific TAK1‐deleted mice

Hepatocyte death is associated with liver inflammation, fibrosis and hepatocellular carcinoma (HCC). Damaged cells trigger inflammation through activation of Toll‐like receptors (TLRs). Although the role of TLR4 in HCC development has been reported, the role of TLR9 in the development of HCC remains elusive. To investigate the role of TLR4 and TLR9 signaling in liver inflammation‐fibrosis‐cancer axis, we took advantage of mice with hepatic deletion of transforming growth factor‐β‐activated kinase 1 (Tak1ΔHep) that develop spontaneous liver injury, inflammation, fibrosis, and HCC, recapitulating the pathology of human HCC. We generated double knockout mice lacking genes of our interest with hepatic Tak1. Tak1ΔHep mice and Tlr4‐deficient Tak1ΔHep mice had similar serum ALT levels, but Tlr4‐deficient Tak1ΔHep mice exhibited significantly reduced macrophage infiltration, myofibroblast activation and tumor formation. Ablation of TLR9 reduced spontaneous liver injury, inflammation, fibrosis, and cancer development in Tak1ΔHep mice. In addition, the common adaptor, myeloid differentiation factor 88 (MyD88)‐deficient Tak1ΔHep mice also attenuated liver injury, macrophage recruitment, collagen deposition, and tumor growth compared with control Tak1ΔHep mice. Genetic ablation of TNF receptor type I (TNFR) in Tak1ΔHep mice remarkably reduced liver inflammation‐fibrosis‐cancer axis. Surprisingly, disruption of interleukin‐1 receptor (IL‐1R) had no effect on liver injury and tumor formation, although Il1r‐deficient Tak1ΔHep showed attenuated macrophage infiltration and collagen deposition. In conclusion, TLR4‐ and TLR9‐MyD88 are driving forces of progression to HCC accompanied by liver inflammation and fibrosis in Tak1ΔHep mice. Importantly, TLR4 and TLR9 downstream TNFR, but not IL‐1R signaling is crucial for the development of HCC in Tak1ΔHep mice.
Cortical-Inspired Open-Bigram Representation for Handwritten Word Recognition

Recent research in the cognitive process of reading hypothesized that we do not read words by sequentially recognizing letters, but rather by identifing open-bigrams, i.e. couple of letters that are not necessarily next to each other. In this paper, we evaluate an handwritten word recognition method based on original open-bigrams representation. We trained Long Short-Term Memory Recurrent Neural Networks (LSTM-RNNs) to predict open-bigrams rather than characters, and we show that such models are able to learn the long-range, complicated and intertwined dependencies in the input signal, necessary to the prediction. For decoding, we decomposed each word of a large vocabulary into the set of constituent bigrams, and apply a simple cosine similarity measure between this representation and the bagged RNN prediction to retrieve the vocabulary word. We compare this method to standard word recognition techniques based on sequential character recognition. Experiments are carried out on two public databases of handwritten words (Rimes and IAM). The bigram decoder results with our bigram decoder are comparable to more conventional decoding methods based on sequences of letters.