Miracle-dz/UniFAR-FTUs huggingface dataset:
Expectations in the Ultimatum Game: Distinct Effects of Mean and Variance of Expected Offers

Being treated fairly by others is an important need in everyday life. Experimentally, fairness can be studied using the Ultimatum Game, where the decision to reject a low, but non-zero offer is seen as a way to punish the other player for an unacceptable offer. The canonical explanation of such behavior is inequity aversion: people prefer equal outcomes over personal gains. However, there is abundant evidence that people's decision to reject a low offer can be changed by contextual factors and their emotional state, which cannot be explained by the inequity aversion model. Here, we expand a recent alternative explanation: rejections are driven by deviations from expectations: the larger the difference between the actual offer and the expected offer, the more likely one is to reject the offer. Specifically, we provided participants with explicit information on what kind of offers to expect using histograms depicting distribution of offers given in a previous experiment by the same proposers. Crucially, we showed four different distributions, manipulating both the mean and the variance of these expected sets of offers. We found that 50% of our participants clearly and systematically changed their behavior as a function of their expectations (11% followed the standard-economic model of pure self-interest and 39% where not distinguishable from the inequity-aversion model). Using a logistic mixed-model analysis, we found that the mean and variance differently affect the decision to reject an offer. Specifically, the mean expected offer affected the threshold of what offers are acceptable, while the expected variance of offers changed how strict participants were about this threshold. Together, these results suggest that social expectations have a more complex nature as current theories propose.
A System-Level Thermal Simulator with Automatic Meshing Techniques

The grid structure of most numerical thermal simulators has to be designed artificially. Designers might need to try many different grid structures for getting accurate thermal profiles, and, hence, waste a great of runtime. In order to solve this problem, this work presents a system-level thermal simulator, DeNAFE, which can adaptively mesh thermal grids automatically. First, we develop and employ a fast thermal estimation engine to roughly obtain the thermal profile of the system. Then, with this thermal profile, we propose and utilize an adaptive meshing procedure to decide its grid structure and perform thermal simulation. Compared with a commercial tool, ANSYS Icepak, the experimental results show that the speedup of DeNAFE can be up to two orders of magnitude with only 6.09% maximum error for all chips in the steady-state thermal simulation. Furthermore, the error of chips is less than 5.25%, the error of screen/skin is less than 6.03%, and the speedup can be over 171.12 times in the transient simulation.
Human Plasmablast Migration Toward CXCL12 Requires Glucose Oxidation by Enhanced Pyruvate Dehydrogenase Activity via AKT

Migration of human plasmablast to the bone marrow is essential for the final differentiation of plasma cells and maintenance of effective humoral immunity. This migration is controlled by CXCL12/CXCR4-mediated activation of the protein kinase AKT. Herein, we show that the CXCL12-induced migration of human plasmablasts is dependent on glucose oxidation. Glucose depletion markedly inhibited plasmablast migration by 67%, and the glucose analog 2-deoxyglucose (2-DG) reduced the migration by 53%; conversely, glutamine depletion did not reduce the migration. CXCL12 boosted the oxygen consumption rate (OCR), and 2-DG treatment significantly reduced the levels of all measured tricarboxylic acid (TCA) cycle intermediates. AKT inhibitors blocked the CXCL12-mediated increase of OCR. CXCL12 enhanced the pyruvate dehydrogenase (PDH) activity by 13.5-fold in an AKT-dependent manner to promote mitochondrial oxidative phosphorylation. The knockdown and inhibition of PDH confirmed its indispensable role in CXCL12-induced migration. Cellular ATP levels fell by 91% upon exposure to 2-DG, and the mitochondrial ATP synthase inhibitor oligomycin inhibited CXCL12-induced migration by 85%. Low ATP levels inhibited the CXCL12-induced activation of AKT and phosphorylation of myosin light chains by 42%, which are required for cell migration. Thus, we have identified a mechanism that controls glucose oxidation via AKT signaling and PDH activation, which supports the migration of plasmablasts. This mechanism can provide insights into the proper development of long-lived plasma cells and is, therefore, essential for optimal humoral immunity. To our knowledge, this study is the first to investigate metabolic mechanisms underlying human plasmablast migration toward CXCL12.
High-Capacity Symmetric Dynamic Indoor Optical Wireless Communication Equipped With User Localization

We report on a novel all-optical system for ultra-high-capacity indoor wireless communication with centralized light sources. Using optical cross-connect and reflective modulator photonic chips, bidirectional dynamic indoor wireless networks equipped with localization and tracking functionalities are realized. This novel system allows us to harvest the ultimate bandwidth of optical communication in the wireless domain in a more cost-/energy-efficient manner. Bidirectional transmission capacities in excess of 40 Gb/s per user are demonstrated experimentally.
Cooperative Multigroup Multicast Transmission in Integrated Terrestrial-Satellite Networks

In this paper, we investigate the downlink cooperative multigroup multicast transmission in the integrated terrestrial-satellite network, in which base stations (BSs) and the satellite provide the multicast service for ground users in a cooperative manner while reusing the entire bandwidth. For both terrestrial BSs and the satellite, multiantennas are equipped and beamforming techniques are utilized for improving the system performance. Based on the architecture, we formulate a weighted max–min fair (MMF) beamforming design problem to jointly optimize the beamforming vectors of BSs and the satellite, which is solved based on the relation between the quality of service problem and the MMF problem. When it comes to the large scale case, where large numbers of BSs are distributed within the coverage of the satellite, we propose a time division cooperative multigroup multicast scheme consisting of two phases for the BSs and the satellite. Then, an iterative algorithm is proposed to solve the weighted MMF problem in the time division case. Finally, numerical results are provided to evaluate the cooperative multicast schemes as well as the proposed algorithms.
Remote Estimation Over a Packet-Drop Channel With Markovian State

We investigate a remote estimation problem in which a transmitter observes a Markov source and chooses the power level to transmit it over a time-varying packet-drop channel. The channel is modeled as a channel with Markovian state where the packet drop probability depends on the channel state and the transmit power. A receiver observes the channel output and the channel state and estimates the source realization. The receiver also feeds back the channel state and an acknowledgment for successful reception to the transmitter. We consider two models for the source—finite state Markov chains and first-order autoregressive processes. For the first model, using ideas from team theory, we establish the structure of optimal transmission and estimation strategies and identify a dynamic program to determine optimal strategies with that structure. For the second model, we assume that the noise process has unimodal and symmetric distribution. Using ideas from majorization theory, we show that the optimal transmission strategy is symmetric and monotonic and the optimal estimation strategy is like Kalman filter. Consequently, when there are a finite number of power levels, the optimal transmission strategy may be described using thresholds that depend on the channel state. Finally, we propose a simulation-based approach (renewal Monte Carlo) to compute the optimal thresholds and optimal performance and elucidate the algorithm with an example.
Performance analysis of an earth-satellite intensity modulated FSO link in the presence of turbulence and varying path loss

Using Gamma-Gamma distribution to describe the atmospheric turbulences, we present a wireless optical communication model incorporating intensity modulation/direct detection (IM/DD) technique. Specifically, we have derived the closed form expressions for the cumulative distribution function (CDF) and the probability distribution function (PDF) for an FSO transmission system. Accounting for the atmospheric path losses and Mie scattering, we offer the closed form expressions for different performance parameters of wireless optical transmission system such as, outage probability, bit error rate for different binary modulation schemes and ergodic capacity, all in terms of Meijer's G function. Moreover, utilizing the asymptotic approximation of Meijer's G function, the outage probability and bit error rate are presented in the form of simple elementary functions at higher values of signal-to-noise ratio (SNR).
On the Performances of POPS-PHYDYAS Waveforms

The necessity of supporting the expected 5G's services, which reveal major limits to ensure strict synchronism and orthogonality, has brought researchers to conceive new waveforms. Recently, the Ping-pong Optimized Pulse Shaping (POPS) algorithm [1] has been introduced as a powerful tool to efficiently design waveforms candidates for 5G. In this paper, we characterize a new design of PHYDYAS waveforms, namely POPS-PHYDYAS, which it is based on the mix of the POPS algorithm and the PHYDYAS waveform [2]. These new waveforms ensure higher SINR level compared to the original PHYDYAS waveforms, as they are conceived by Mirabbasi-Martin [3]. Performances of POPS-PHYDYAS are compared to several 5G waveforms in terms of SIR, OOB emissions and BER.
pH plays a role in the mode of action of trimethoprim on Escherichia coli

Metabolomics-based approaches were applied to understand interactions of trimethoprim with Escherichia coli K-12 at sub-minimum inhibitory concentrations (MIC≈0.2, 0.03 and 0.003 mg L-1). Trimethoprim inhibits dihydrofolate reductase and thereby is an indirect inhibitor of nucleic acid synthesis. Due to the basicity of trimethoprim, two pH levels (5 and 7) were selected which mimicked healthy urine pH. This also allowed investigation of the effect on bacterial metabolism when trimethoprim exists in different ionization states. UHPLC-MS was employed to detect trimethoprim molecules inside the bacterial cell and this showed that at pH 7 more of the drug was recovered compared to pH 5; this correlated with classical growth curve measurements. FT-IR spectroscopy was used to establish recovery of reproducible phenotypes under all 8 conditions (3 drug levels and control in 2 pH levels) and GC-MS was used to generate global metabolic profiles. In addition to finding direct mode-of-action effects where nucleotides were decreased at pH 7 with increasing trimethoprim levels, off-target pH-related effects were observed for many amino acids. Additionally, stress-related effects were observed where the osmoprotectant trehalose was higher at increased antibiotic levels at pH 7. This correlated with glucose and fructose consumption and increase in pyruvate-related products as well as lactate and alanine. Alanine is a known regulator of sugar metabolism and this increase may be to enhance sugar consumption and thus trehalose production. These results provide a wider view of the action of trimethoprim. Metabolomics indicated alternative metabolism areas to be investigated to further understand the off-target effects of trimethoprim.
Alzheimer’s disease and blood-based biomarkers – potential contexts of use

Alzheimer’s disease (AD) is an irreversible, incurable, progressive neurodegenerative illness, where dementia symptoms gradually worsen over a number of years. The research of validated biomarkers for AD is essential to improve diagnosis and accelerate the development of new therapies. Biochemical markers including neuroimaging could facilitate diagnosis, predict AD progression from a pre-AD state of mild cognitive impairment, and be used to detect the efficacies of disease-modifying therapies. Established biomarkers of AD from cerebrospinal fluid and neuroimaging are highly accurate, but barriers to clinical implementation exist. The focus on blood-based AD biomarkers has grown exponentially during the past few decades. An ideal diagnostic test for AD should be noninvasive and easily applicable. Clinical cost-effectiveness also needs to be established.
A DfT Insertion Methodology to Scannable Q-Flop Elements

The Q-Flop is an alternative memory element for designs that are prone to metastability. It has been substantially explored by past research work, specially in synchronization schemes. However, there is very limited support to test insertion on these critical components. This brief presents a testable Q-flop cell and a methodology to integrate it to standard synthesis and DfT flows, allowing automated scan insertion using conventional sequential cells and commercial design automation solutions. Experimental results explore the tradeoffs of the proposed cell in terms of silicon area, energy, and power when compared to the original Q-flop.
Multiple transgressions and slow evolution shape the phylogeographic pattern of the blind cave-dwelling shrimp Typhlocaris

Background Aquatic subterranean species often exhibit disjunct distributions, with high level of endemism and small range, shaped by vicariance, limited dispersal, and evolutionary rates. We studied the disjunct biogeographic patterns of an endangered blind cave shrimp, Typhlocaris, and identified the geological and evolutionary processes that have shaped its divergence pattern. Methods We collected Typlocaris specimens of three species (T. galilea, T. ayyaloni, and T. salentina), originating from subterranean groundwater caves by the Mediterranean Sea, and used three mitochondrial genes (12S, 16S, cytochrome oxygnese subunit 1 (COI)) and four nuclear genes (18S, 28S, internal transcribed spacer, Histon 3) to infer their phylogenetic relationships. Using the radiometric dating of a geological formation (Bira) as a calibration node, we estimated the divergence times of the Typhlocaris species and the molecular evolution rates. Results The multi-locus ML/Bayesian trees of the concatenated seven gene sequences showed that T. salentina (Italy) and T. ayyaloni (Israel) are sister species, both sister to T. galilea (Israel). The divergence time of T. ayyaloni and T. salentina from T. galilea was 7.0 Ma based on Bira calibration. The divergence time of T. ayyaloni from T. salentina was 5.7 (4.4–6.9) Ma according to COI, and 5.8 (3.5–7.2) Ma according to 16S. The computed interspecific evolutionary rates were 0.0077 substitutions/Myr for COI, and 0.0046 substitutions/Myr for 16S. Discussion Two consecutive vicariant events have shaped the phylogeographic patterns of Typhlocaris species. First, T. galilea was tectonically isolated from its siblings in the Mediterranean Sea by the arching uplift of the central mountain range of Israel ca. seven Ma. Secondly, T. ayyaloni and T. salentina were stranded and separated by a marine transgression ca. six Ma, occurring just before the Messinian Salinity Crisis. Our estimated molecular evolution rates were in one order of magnitude lower than the rates of closely related crustaceans, as well as of other stygobiont species. We suggest that this slow evolution reflects the ecological conditions prevailing in the highly isolated subterranean water bodies inhabited by Typhlocaris.
Resistance to commonly used insecticides and phosphine fumigant in red palm weevil, Rhynchophorus ferrugineus (Olivier) in Pakistan

The red palm weevil Rhynchophorus ferrugineus (Olivier) is an important pest of date palms in many regions of the world. This paper reports the first survey of insecticide resistance in field populations of R. ferrugineus in Pakistan which were collected from seven date palm growing areas across Punjab and Khyber Pakhtunkhwa (KPK) provinces, Pakistan. The resistance was assessed by the diet incorporation method against the formulated commonly used chemical insecticides profenophos, imidacloprid, chlorpyrifos, cypermethrin, deltamethrin, spinosad, lambda-cyhalothrin and a fumigant phosphine. Elevated levels of resistance were recorded for cypermethrin, deltamethrin and phosphine after a long history of insecticide use in Pakistan. Resistance Ratios (RRs) were 63- to 79-fold for phosphine, 16- to 74-fold for cypermethrin, 13- to 58-fold for deltamethrin, 2.6- to 44-fold for profenophos, 3- to 24-fold for chlorpyrifos, 2- to 12-fold for lambda-cyhalothrin and 1- to 10-fold for spinosad compared to a susceptible control line. Resistant R. ferrugineus populations were mainly found in southern Punjab and to some extent in KPK. The populations from Bahawalpur, Vehari, Layyah and Dera Ghazi Khan were most resistant to chemical insecticides, while all populations exhibited high levels of resistance to phosphine. Of the eight agents tested, lower LC50 and LC90 values were recorded for spinosad and lambda-cyhalothrin. These results suggest that spinosad and lambda-cyhalothrin exhibit unique modes of action and given their better environmental profile, these two insecticides could be used in insecticide rotation or assist in phasing out the use of older insecticides. A changed pattern of both insecticides can be used sensibly be recommended without evidence of dose rates and frequencies used.
Using Convolutional Neural Networks for Distance Estimation between Dedicated Short-Range Communications Equipped Vehicles

This work explores the feasibility of leveraging deep learning methods for performing distance estimation between two Dedicated Short-Range Communications (DSRC) equipped vehicles. Real world DSRC data was collected from mixed environments. The data was used to perform hyperparameter search for constructing and training multiple Convolutional Deep Neural Networks (CDNN). Performances of several NN configurations were compared along with Ordinary Least Squares (OLS) regression. Results show that for shorter distances, NN estimation performance is similar to that of OLS regression. While for longer distances, CDNN performance shows improvement over regression in the average. These results suggest that distance estimation using CDNN is plausible. This method combined with other sensors may contribute to improved positioning in challenging environments.
Alcohol consumption and future hospital usage: The EPIC-Norfolk prospective population study

Background Heavy drinkers of alcohol are reported to use hospitals more than non-drinkers, but it is unclear whether light-to-moderate drinkers use hospitals more than non-drinkers. Objective We examined the relationship between alcohol consumption in 10,883 men and 12,857 women aged 40–79 years in the general population and subsequent admissions to hospital and time spent in hospital. Methods Participants from the EPIC-Norfolk prospective population-based study were followed for ten years (1999–2009) using record linkage. Results Compared to current non-drinkers, men who reported any alcohol drinking had a lower risk of spending more than twenty days in hospital multivariable adjusted OR 0.80 (95%CI 0.68–0.94) after adjusting for age, smoking status, education, social class, body mass index and prevalent diseases. Women who were current drinkers were less likely to have any hospital admissions multivariable adjusted OR 0.84 (95%CI 0.74–0.95), seven or more admissions OR 0.77 (95% CI 0.66–0.88) or more than twenty hospital days OR 0.70 (95%CI 0.62–0.80). However, compared to lifelong abstainers, men who were former drinkers had higher risk of any hospital admissions multivariable adjusted OR 2.22 (95%CI 1.51–3.28) and women former drinkers had higher risk of seven or more admissions OR 1.30 (95%CI 1.01–1.67). Conclusion Current alcohol consumption was associated with lower risk of future hospital usage compared with non-drinkers in this middle aged and older population. In men, this association may in part be due to whether former drinkers are included in the non-drinker reference group but in women, the association was consistent irrespective of the choice of reference group. In addition, there were few participants in this cohort with very high current alcohol intake. The measurement of past drinking, the separation of non-drinkers into former drinkers and lifelong abstainers and the choice of reference group are all influential in interpreting the risk of alcohol consumption on future hospitalisation.
Table tennis playing styles require specific energy systems demands

The aim of the present study was to investigate the differences in energy system contributions and temporal variables between offensive and all-round playing styles. Fifteen male table tennis players (Offensive players: N = 7; All-round players: N = 8) participated in the study. Matches were monitored by a portable gas analyzer and the blood lactate responses was also measured. The contributions of the oxidative (WOXID), phosphagen (WPCr), and glycolytic (W[La]) energy systems were assumed as the oxygen consumption measured during the matches above of baseline value, the fast component of excess post-exercise oxygen consumption (EPOCFAST) measured after the matches, and the net of blood lactate concentration (Δ[La]), respectively. Energy systems contributions were not significantly different between the offensive and all-round playing styles (WOXID: 96.1±2.0 and 97.0±0.6%, P = 0.86; WPCr: 2.7±1.7 and 2.0±0.6%, P = 0.13; W[La]: 1.2±0.5 and 1.0±0.7%, P = 0.95; respectively), however, magnitude-based analysis of WPCr presented Likely higher contribution for offensive compared to all-round players. Regarding temporal variables, only rate of shots presented higher values for offensive when compared to all-round players (P = 0.03), while the magnitude-based analysis presented Very likely lower, Likely lower and Likely higher outcomes of rate of shots, WPCr and maximal oxygen consumption, respectively, for all-round players. Strong negative correlation was verified for offensive players between number of shots and WPCr (r = -0.86, P = 0.01), while all-round players showed strong correlations between rally duration, WOXID (r = 0.76, P = 0.03) and maximal oxygen consumption (r = 0.81, P = 0.03). Therefore, despite no differences in energy system contributions for offensive and all-round players, different playing styles seems to requires specific energy systems demands.