Miracle-dz/UniFAR-FTUs huggingface dataset:
PAndAS’ CUBS: DISCOVERY OF TWO NEW DWARF GALAXIES IN THE SURROUNDINGS OF THE ANDROMEDA AND TRIANGULUM GALAXIES

We present the discovery of two new dwarf galaxies, Andromeda XXI and Andromeda XXII, located in the surroundings of the Andromeda and Triangulum galaxies (M31 and M33). These discoveries stem from the first year data of the Pan-Andromeda Archaeological Survey, a photometric survey of the M31/M33 group conducted with the Megaprime/MegaCam Wide-Field Camera mounted on the Canada–France–Hawaii Telescope. Both satellites appear as spatial overdensities of stars which, when plotted in a color-magnitude diagram, follow metal-poor, [Fe/H] = −1.8, red giant branches at the distance of M31/M33. Andromeda XXI is a moderately bright dwarf galaxy (MV = −9.9 ± 0.6), albeit with low surface brightness, emphasizing again that many relatively luminous M31 satellites still remain to be discovered. It is also a large satellite, with a half-light radius close to 1 kpc, making it the fourth largest Local Group dwarf spheroidal galaxy after the recently discovered Andromeda XIX, Andromeda II, and Sagittarius around the Milky Way, and supports the trend that M31 satellites are larger than their Milky Way counterparts. Andromeda XXII is much fainter (MV = −6.5 ± 0.8) and lies a lot closer in projection to M33 than it does to M31 (42 versus 224 kpc), suggesting that it could be the first Triangulum satellite to be discovered. Although this is a very exciting possibility in the context of a past interaction of M33 with M31 and the fate of its satellite system, a confirmation will have to await a good distance estimate to confirm its physical proximity to M33. Along with the dwarf galaxies found in previous surveys of the M31 surroundings, these two new satellites bring the number of dwarf spheroidal galaxies in this region to 20.
Let them eat fruit! The effect of fruit and vegetable consumption on psychological well-being in young adults: A randomized controlled trial

This study tested the psychological benefits of a 14-day preregistered clinical intervention to increase fruit and vegetable (FV) consumption in 171 low-FV-consuming young adults (67% female, aged 18–25). Participants were randomly assigned into a diet-as-usual control condition, an ecological momentary intervention (EMI) condition involving text message reminders to increase their FV consumption plus a voucher to purchase FV, or a fruit and vegetable intervention (FVI) condition in which participants were given two additional daily servings of fresh FV to consume on top of their normal diet. Self-report outcome measures were depressive symptoms and anxiety measured pre- and post-intervention, and daily negative and positive mood, vitality, flourishing, and flourishing behaviors (curiosity, creativity, motivation) assessed nightly using a smartphone survey. Vitamin C and carotenoids were measured from blood samples pre- and post-intervention, and psychological expectancies about the benefits of FV were measured post-intervention to test as mediators of psychological change. Only participants in the FVI condition showed improvements to their psychological well-being with increases in vitality, flourishing, and motivation across the 14-days relative to the other groups. No changes were found for depressive symptoms, anxiety, or mood. Intervention benefits were not mediated by vitamin C, carotenoids, or psychological expectancies. We conclude that providing young adults with high-quality FV, rather than reminding them to eat more FV (with a voucher to purchase FV), resulted in significant short-term improvements to their psychological well-being. These results provide initial proof-of-concept that giving young adults fresh fruit and vegetables to eat can have psychological benefits even over a brief period of time. Trial registration: Australian New Zealand Clinical Trials Registry ACTRN12615000183583
The Evidence-Based Group Psychotherapist

ABSTRACT Growing attention is appropriately afforded to the importance of practicing group psychotherapy in an evidence-based fashion. Pressures with regard to accountability, efficiency, and effectiveness make this an imperative in contemporary psychotherapy. This article illustrates and operationalizes factors that contribute to enhanced group psychotherapist effectiveness; identifies approaches that maximize therapeutic opportunities within the client-therapist relationship in the here and now of the group therapy setting; and illustrates the principles of therapeutic metacommunication within the therapeutic relationship and explores therapist use of self and judicious therapist transparency. An evidence-informed approach guides these articulations and the article illustrates these principles with a clinical vignette and discussion
Approaches For Automated Detection And Classification Of Masses In Mammograms

Breast cancer is one of the most common cancer among women around the world. Several techniques are available for detection of breast cancer. Mammography is one of the most effective tools for early detection. The goal of this research is to increase the diagnostic accuracy of image processing and machine learning techniques for optimum classification between normal and abnormalities in digital mammograms. GLCM texture feature extractions are known to be the most common and powerful techniques for texture analysis. This paper presents an evaluation and comparison of the performance of two different classification methods used to classify the normal and abnormal patterns. The experimental result suggest that Artificial Neural Network is outperformed the other method.
The Association between Hematological Parameters and Insulin Resistance Is Modified by Body Mass Index – Results from the North-East Italy MoMa Population Study

Objective Increments in red blood cell count (RBC), hemoglobin (Hb) and hematocrit (Ht) levels are reportedly associated with higher insulin resistance (IR). Obesity may cause IR, but underlying factors remain incompletely defined, and interactions between obesity, hematological parameters and IR are incompletely understood. We therefore determined whether: 1) BMI and obesity per se are independently associated with higher RBC, hemoglobin and hematocrit; 2) hematological parameters independently predict insulin resistance in obese individuals. Design and Methods We investigated the associations between BMI, hematological parameters and insulin resistance as reflected by homeostasis model assessment (HOMA) in a general population cohort from the North-East Italy MoMa epidemiological study (M/F = 865/971, age = 49±1). Results In all subjects, age-, sex- and smoking-adjusted hematological parameters were positively associated with BMI in linear regression (P<0.05), but not after adjustment for HOMA or waist circumference (WC) and potential metabolic confounders. No associations were found between hematological parameters and BMI in lean, overweight or obese subgroups. Associations between hematological parameters and HOMA were conversely independent of BMI in all subjects and in lean and overweight subgroups (P<0.01), but not in obese subjects alone. Conclusions In a North-East Italy general population cohort, obesity per se is not independently associated with altered RBC, Hb and Ht, and the association between BMI and hematological parameters is mediated by their associations with abdominal fat and insulin resistance markers. High hematological parameters could contribute to identify insulin resistance in non-obese individual, but they do not appear to be reliable insulin resistance biomarkers in obese subjects.
Neural networks for blind decorrelation of signals

We analyze and extend a class of adaptive networks for second-order blind decorrelation of instantaneous signal mixtures. First, we compare the performance of the single-layer neural network employing global knowledge of the adaptive coefficients with a similar structure whose coefficients are adapted via local output connections. Through statistical analyzes, the convergence behaviors and stability bounds for the algorithms' step sizes are studied and derived. Second, we analyze the behaviors of locally adaptive multilayer decorrelation networks and quantify their performances for poorly conditioned signal mixtures. Third, we derive a robust locally adaptive network structure based on a posteriori output signals that remains stable for any step-size value. Finally, we present an extension of the locally adaptive network for linear-phase temporal and spatial whitening of multichannel signals. Simulations verify the analyses and indicate the usefulness of the locally adaptive networks for decorrelating signals in space and time.
CMOS neurostimulation ASIC with 100 channels, scaleable output, and bidirectional radio-frequency telemetry

100-channel neurostimulation circuit comprising a complementary metal oxide semiconductor (CMOS), application-specific integrated circuit (ASIC) has been designed, constructed and tested. The ASIC forms a significant milestone and an integral component of a 100-electrode neurostimulation system being developed by the authors. The system comprises an externally worn transmitter and a body implantable stimulator. The purpose of the system is to communicate both data and power across tissue via radio-frequency (RF) telemetry such that externally programmable, constant current, charge balanced, biphasic stimuli may be delivered to neural tissue at 100 unique sites. An intrinsic reverse telemetry feature of the ASIC has been designed such that information pertaining to the device function, reconstruction of the stimulation voltage waveform, and the measurement of impedance may be obtained through noninvasive means. To compensate for the paucity of data pertaining to the stimulation thresholds necessary in evoking a physiological response, the ASIC has been designed with scaleable current output. The ASIC has been designed primarily as a treatment of degenerative disorders of the retina whereby the 100 channels are to be utilized in the delivery of a pattern of stimuli of varying intensity and or duty cycle to the surviving neural tissue of the retina. However, it is conceivable that other fields of neurostimulation such as cochlear prosthetics and functional electronic stimulation may benefit from the employment of the system.
Does consistency matter? perception and persuasiveness of value appeals in populist communication

Although research has shown that political actors benefit from appealing to values that resonate with their audience’s preferences, it remains an open question to what extent this can be exploited. How do individuals react to value appeals that are inconsistent with the communicator’s value reputation? This paper examines this question in the context of right-wing populist parties, who are strongly associated with conservation values. In two experiments, the effects of consistent and inconsistent value appeals on perception (study 1) and persuasion (study 2) are investigated. It is expected that consistent values will be perceived stronger than inconsistent values, but that both kind of Appeals can be persuasive when they match with the audience’s value orientation. The results confirm these expectations and show that especially individuals with lower formal education can be persuaded to support right-wing populist Claims when these are promoted with inconsistent but matching value appeals.
Information Communication in Financial Markets

Empirical evidence shows word-of-mouth communication has real effects on trading patterns in financial markets. On top of that, the social network through which the information conveys also plays a crucial role. We propose a framework that allows informed traders to directly and truthfully communicate information in four major social interaction structures represented by circle, tree, star and complete network graphs. In particular, we generalize a la Kyle (1985)’s strategical noisy rational expectation model by incorporating directed information transmission. We highlight that individual exploits information distinctly in different networks, and individual’s influence on market price relies on the network type and position in the network. Despite of the distinction on individual trading behavior and influential power on price, market trading patterns are similar irrespective of the network structures. Trading volume, price volatility and the information efficiency of price are all higher in networks than their counterparts in conventional models without networks.
Robust FOREX Trading with Deep Q Network (DQN)

Financial trading is one of the most attractive areas in finance. Trading systems development is not an easy task because it requires extensive knowledge in several areas such as quantitative analysis, financial skills, and computer programming. A trading systems expert, as a human, also brings in their own bias when developing the system. There should be another, more effective way to develop the system using artificial intelligence. The aim of this study was to compare the performance of AI agents to the performance of the buy-and-hold strategy and the expert trader. The tested market consisted of 15 years of the Forex data market, from two currency pairs (EURUSD, USDJPY) obtained from Dukascopy Bank SA Switzerland. Both hypotheses were tested with a paired t-Test at the 0.05 significance level. The findings showed that AI can beat the buy & hold strategy with significant superiority, in FOREX for both currency pairs (EURUSD, USDJPY), and that AI can also significantly outperform CTA (experienced trader) for trading in EURUSD. However, the AI could not significantly outperform CTA for USDJPY trading. Limitations, contributions, and further research were recommended.
Inhibiting translation elongation can aid genome duplication in Escherichia coli

Abstract Conflicts between replication and transcription challenge chromosome duplication. Escherichia coli replisome movement along transcribed DNA is promoted by Rep and UvrD accessory helicases with Δrep ΔuvrD cells being inviable under rapid growth conditions. We have discovered that mutations in a tRNA gene, aspT, in an aminoacyl tRNA synthetase, AspRS, and in a translation factor needed for efficient proline–proline bond formation, EF-P, suppress Δrep ΔuvrD lethality. Thus replication-transcription conflicts can be alleviated by the partial sacrifice of a mechanism that reduces replicative barriers, namely translating ribosomes that reduce RNA polymerase backtracking. Suppression depends on RelA-directed synthesis of (p)ppGpp, a signalling molecule that reduces replication-transcription conflicts, with RelA activation requiring ribosomal pausing. Levels of (p)ppGpp in these suppressors also correlate inversely with the need for Rho activity, an RNA translocase that can bind to emerging transcripts and displace transcription complexes. These data illustrate the fine balance between different mechanisms in facilitating gene expression and genome duplication and demonstrate that accessory helicases are a major determinant of this balance. This balance is also critical for other aspects of bacterial survival: the mutations identified here increase persistence indicating that similar mutations could arise in naturally occurring bacterial populations facing antibiotic challenge.
Predictors of poor treatment response to additional CBT in real panic disorder patients: The role of DLPF, orbitofrontal cortex, parietal lobule, frontal eye field and amygdala in PD.

OBJECTIVE Previous functional brain imaging studies have described various and contradictory activation findings in patients with panic disorder (PD). Our study focused on patients with a chronic PD, who were investigated and treated in a conventional manner, which represents the real PD patients in clinical practice. METHODS Continuing their medication, patients were included in a six-week cognitive-behavioral therapy (CBT) program in the psychiatry department. At the onset of the study, participants underwent clinical evaluation using standard scales and were examined using fMRI while listening to verbal threat-related stimuli contrasted to neutral words. According to the therapeutic outcome, they were subsequently divided into two groups, responders, and nonresponders and the two groups were mutually compared. RESULTS In non-responders compared to responders, we found increased pre-treatment activation in dorsolateral prefrontal cortex bilaterally, left orbitofrontal cortex, left frontal eye field, right parietal lobule and left amygdala. In addition, both groups showed negative fMRI BOLD correlation with BAI improvement and positive correlation with CGI improvement across the ROIs. We suggest that DLPFC over-activation may reveal a lack of cognitive control over emotional processing, which makes subsequent CBT less effective. CONCLUSION Despite several limitations, we found neuroimaging predictors of poor CBT response, under the conditions of standard clinical practice, in real PD patients.
WCRP Modelling Strategy Developments

CLIVAR is an international research programme dealing with climate variability and predictability on time-sales from months to centuries. WCRP is pleased to report on the newly formed WCRP Modelling Council in this special issue of CLIVAR Exchanges that is devoted to the exciting results from WCRP sponsored climate modelling activities. The WCRP Modelling Council is formed to coordinate research on development and use of climate and Earth system models across its four major projects (CliC, CLIVAR, GEWEX and SPARC), and its sister international global change research programs such as IGBP and WWRP. The Joint Scientific Committee (JSC) of WCRP initiated discussion on the formation of the Modelling Council in its 31st meeting in 2010 in Antalya, Turkey, and recently endorsed its formation at its 32nd meeting in Exeter, United Kingdom. The Council will replace the WCRP Modelling Panel which sunset in 2009. There has been considerable discussion within WCRP and with its sister research programmes on the functions and structure of the Council that are captured in the JSC report available on the WCRP website: discussions all took place in the context of WCRP visioning for its future priorities and direction. The purpose of this Council is to promote: t 5IFHSFBUFSVTFPGPCTFSWBUJPOTBOESFTVMUTPGQSPDFTT studies in models; t . PEFMEFWFMPQNFOUBOEJNQSPWFNFOUT t $PMMBCPSBUJPOBNPOHTUWBSJPVTDMJNBUFTDJFODF communities (including numerical weather prediction (NWP), seasonal to interannual prediction and climate projection as well as those dealing with biogeochemistry, air quality, terrestrial ecology, etc.); t "QQMJDBUJPOPGNPEFMTUPQSPCMFNTPGTPDJFUBMSFMFWBODF quantifying uncertainties and making sure they are well communicated and understood; Five small teams of experts were identified and each team was asked to develop a short concept paper on the four scientific and technical themes identified above. The fifth team was asked to develop a governance concept for coordination of the functions associated with the first four themes, through a grass-root process and across the entire WCRP Projects and Program activities. The initial draft of the five concept papers were distributed for review and comment, and further refined as a result of a special modelling coordination meeting that was convened in November 2010, in Paris, France. A WCRP report (WCRP Series Report No.133 WMO/TD-N°.1569) from this workshop includes the five concept papers plus the overall summary of the deliberations that is provided below: Human activity has changed our climate over the past century , and further change is inevitable over the next several decades, even if strong mitigation actions are taken. It is thus …
Credit scoring with boosted decision trees

The enormous growth experienced by the credit industry has led researchers to develop sophisticated credit scoring models that help lenders decide whether to grant or reject credit to applicants. This paper proposes a credit scoring model based on boosted decision trees, a powerful learning technique that aggregates several decision trees to form a classifier given by a weighted majority vote of classifications predicted by individual decision trees. The performance of boosted decision trees is evaluated using two publicly available credit card application datasets. The prediction accuracy of boosted decision trees is benchmarked against two alternative data mining techniques: the multilayer perceptron and support vector machines. The results show that boosted decision trees are a competitive technique for implementing credit scoring models.
Polar Coding for the General Wiretap Channel With Extensions to Multiuser Scenarios

Information-theoretic work for wiretap channels is mostly based on random coding schemes. Designing practical coding schemes to achieve information-theoretic secrecy is an important problem. By applying two recently developed techniques for polar codes, namely, universal polar coding and polar coding for asymmetric channels, we propose a polar coding scheme to achieve the secrecy capacity of the general wiretap channel. We then apply this coding scheme to achieve the best-known inner bounds for the multiple access wiretap channel (MAC-WTC), and the broadcast and interference channels with confidential messages (BC-CM and IC-CM).
Human Rad51 filaments on double- and single-stranded DNA: correlating regular and irregular forms with recombination function

Recombinase proteins assembled into helical filaments on DNA are believed to be the catalytic core of homologous recombination. The assembly, disassembly and dynamic rearrangements of this structure must drive the DNA strand exchange reactions of homologous recombination. The sensitivity of eukaryotic recombinase activity to reaction conditions in vitro suggests that the status of bound nucleotide cofactors is important for function and possibly for filament structure. We analyzed nucleoprotein filaments formed by the human recombinase Rad51 in a variety of conditions on double-stranded and single-stranded DNA by scanning force microscopy. Regular filaments with extended double-stranded DNA correlated with active in vitro recombination, possibly due to stabilizing the DNA products of these assays. Though filaments formed readily on single-stranded DNA, they were very rarely regular structures. The irregular structure of filaments on single-stranded DNA suggests that Rad51 monomers are dynamic in filaments and that regular filaments are transient. Indeed, single molecule force spectroscopy of Rad51 filament assembly and disassembly in magnetic tweezers revealed protein association and disassociation from many points along the DNA, with kinetics different from those of RecA. The dynamic rearrangements of proteins and DNA within Rad51 nucleoprotein filaments could be key events driving strand exchange in homologous recombination.