Miracle-dz/UniFAR-FTUs huggingface dataset:
Incidental Haptic Sensations Influence Social Judgments and Decisions

Between a Rock and a Hard Judgment In general terms, our sensory and motor pathways mature sooner than the so-called higher cognitive centers, which become fully operational later in life. Might these early somatic communication channels with the outside world influence and become buried within the higher levels of processing involved in forming impressions of other people and deciding how to behave toward them? Ackerman et al. (p. 1712) provide evidence for just such a process by focusing on touch. By manipulating the weight, hardness, or roughness of objects that subjects were exposed to, they were able to bias the social judgments and behaviors of the subjects in unrelated realms, such as assessing the rigidness or seriousness of employees and job applicants. A seat-of-the-pants impression (tactile sensation influencing decisions) is a reality and not just a metaphor. Touch is both the first sense to develop and a critical means of information acquisition and environmental manipulation. Physical touch experiences may create an ontological scaffold for the development of intrapersonal and interpersonal conceptual and metaphorical knowledge, as well as a springboard for the application of this knowledge. In six experiments, holding heavy or light clipboards, solving rough or smooth puzzles, and touching hard or soft objects nonconsciously influenced impressions and decisions formed about unrelated people and situations. Among other effects, heavy objects made job candidates appear more important, rough objects made social interactions appear more difficult, and hard objects increased rigidity in negotiations. Basic tactile sensations are thus shown to influence higher social cognitive processing in dimension-specific and metaphor-specific ways.
An Improved Search Algorithm to Find G-Quadruplexes in Genome Sequences

A growing body of data suggests that the secondary structures adopted by G-rich polynucleotides may be more diverse than previously thought and that the definition of G-quadruplex-forming sequences should be broadened. We studied solution structures of a series of naturally occurring and model single-stranded DNA fragments defying the G3+NL1G3+NL2G3+NL3G3+ formula, which is used in most of the current GQ-search algorithms. The results confirm the GQ-forming potential of such sequences and suggest the existence of new types of GQs. We developed an improved (broadened) GQ-search algorithm (http://niifhm.ru/nauchnye-issledovanija/otdel-molekuljarnoj-biologii-i-genetiki/laboratorija-iskusstvennogo-antitelogeneza/497-2/) that accounts for the recently reported new types of GQs.
Concurrent, Reconfigurable, and Adaptable Oscillators For Multi-Band Multi-Mode Communication Systems

This paper presents the design approach of RCO (reconfigurable concurrent oscillator) using MCPTR (multi-coupled planar transmission line resonators) that simultaneously generates two or more signals of different frequencies that eliminate the need of lossy switches for switching the frequency band, thereby improves the system throughput. The measured phase noise for band#1 (2250-2850 MHz) and band#2 (4600-5900 MHz) are typically better than -108 dBc/Hz at 100 kHz offset from the carrier respectively; and the topology can be extended for higher frequency band.
Continuous speech recognition using Correlation features and structured SVM probability output

One potential area for improvement in continuous speech recognition is the modelling of phoneme transitions (not transition probabilties) arising from the non-stationarity of speech: refined models can then be used to compute probability distributions which can serve as emission probabilities for HMM-based speech recognition systems. In this paper we present our approach to improving phoneme transition modelling. Building on our previous work, we employ a phoneme partition approach (SME: start, middle, and end states) to build a structure of support vector (SV) classifiers as our main discriminative method. For the phoneme classification step, cross correlation features based on MFCC-vectors are computed and classified within the SME structure. Additionally, we make use of a special reproducing kernel build upon the correlation features, thus offering a direct integration into the SV classifiers. This paper discusses the computation of the afore-mentioned probability outputs as well as initial results using these outputs as emission probabilities in HMMs representing phonemes, applied within a standard speech recognition system.
How Useful is Anthropometric History? Some Reflections on Paul Hohenberg’s Recent Presidential Address to the American Economic History Association

In his recent presidential address to the American Economic History Association, Paul Hohenberg argued that anthropometric history does not meet his criteria for useful research in the field of economic history. He considers research useful if (a) it “helps shape one of our underlying disciplines”; b) it contributes “to clear – even fresh – thinking about current, policy-related issues or on-going scholarly debates about the historical past"; and c) it “penetrates the fuzzy realm of identity-shaping popular discourse”. I argue briefly that only a superficial reading of the literature would lead to the conclusion that anthropometric history has not been useful.
Mutation chicken swarm optimization based on nonlinear inertia weight

Considering the problem that chicks only follow the hens to search for food and the roosters has weak global search capability in original chicken swarm optimization (CSO) algorithm, Mutation Chicken Swarm Optimization (MCSO) was proposed on the basis of Nonlinear Inertia Weight. The proposed algorithm first introduces the variation factor in the chicken particle position updating formula and then introduces the non-linear decreasing weight based on a parabola opening upwards in the rooster location update formula to improve the chicken location update formula and the rooster location update formula, thus the mutation chicken swarm optimization based on nonlinear inertia weight is easier to obtain the global optimal solution than original chicken swarm optimization algorithm. The optimization performance of the proposed algorithm was verified by six test function, the experimental results are compared with the chicken swarm optimization and differential evolution (DE) algorithm. Then, the mutation chicken swarm optimization based on nonlinear inertia weigh (NW-MCSO) was applied to the Anti-saccharification activity prediction. The experimental results show that the proposed algorithm has strong global search ability, high precision and better optimization performance compared with chicken swarm algorithm and differential evolution algorithm.
What works? A grounded theory of effective peer mentoring in secondary schools

The current research was carried out by a Trainee Educational Psychologist (TEP) between September 2013 and May 2015 in a large County in South-East England as part of a Doctorate in Child, Community and Educational Psychology. Using critical realism as a guiding epistemological position, the study sought to bring school based peer mentors and mentees voice to the forefront, by exploring their view of what works. The study aimed to offer a framework for understanding and developing peer mentoring relationships and inform safe and effective peer mentoring practice in secondary schools. This study was conducted using grounded theory methodology as a strategy of inquiry. Data was captured from semi structured interviews which were audio recorded, transcribed verbatim and analysed, assisted by MaxQDA. Purposive sampling was used to select nine participants from two secondary schools: of which 4 were peer mentors and 5 were mentees whom had participated in their schools peer mentoring programme during the academic year 2013/14. The BONDS model addresses the delivery of peer mentoring within the context of peer support interventions and secondary educational settings. The acronym ‘BONDS’ represents the data which emerged from grounded theory methodology as 5 integrated mechanisms which mediate effective peer mentoring. The model proposes that effective peer mentoring is synonymous with a nurturing experience characterised by ‘boundaries’ within peer mentoring, the ‘openness’ of the mentee to engage, the mentors abilities to build a safe and supportive relationship, the peer mentor and mentees ‘dual experience’ of the school system and ‘staff contact’ with mentors. This study adds to the limited body of research which explores the views of peer mentors and mentees engaged in peer mentoring programmes in the UK. The implications of the findings are discussed and good practice recommendations are made to inform the work of school staff, Educational Psychology services and other professionals working to support young people through school based peer mentoring. The limitations of the study are also addressed and suggestions are made for future research.
Qualitative Evaluation of the Project P.A.T.H.S. Based on the Perceptions of the Program Participants

Qualitative evaluation was carried out to understand the perceptions of the students participating in the Tier 1 Program of the P.A. T.H. S. Project. Five focus groups based on 43 students recruited from four schools were conducted to generate qualitative data to evaluate the program. With specific focus on how the informants described the program, results showed that the descriptors used were mainly positive in nature. When the informants were invited to name three metaphors that could stand for the program, the related metaphors were basically positive in nature. Finally, the program participants perceived many beneficial effects of the program in different psychosocial domains. Intra- and inter-rater reliability analyses revealed that the coding of the positive or negative nature of the responses was reliable. The present study provides qualitative support for the effectiveness of the Tier 1 Program of the Project P.A. T.H. S. in promoting holistic development in Chinese adolescents in Hong Kong.
Channel Coding and Multiuser Detection for CDMA and Wireless Communications

Next generation wireless communication systems will require support for many different applications as well as improved quality compared to existing second generation systems like GSM (Global System for Mobile communications). Since there will be more users and higher data rates, the capacity must also be increased. This thesis studies channel coding and multiuser detection, two techniques that are of vital importance for designing a flexible system with high capacity and high quality. In the first part of the thesis optimum distance spectrum (ODS) convolutional encoders are presented. These encoders generate maximum free distance codes and have superior information error weights. Results show that the ODS codes outperform previously published maximum free distance codes at no extra cost. We next use the ODS encoders as parent encoders to find large and flexible families of multirate codes. These multirate codes are obtained both by puncturing and nesting of the parent ODS codes, and are shown to perform almost as well as unpunctured codes, and to be well suited for rate-matching in direct-sequence code-division multiple-access (DS-CDMA) systems. A study of the performance of a number of multiuser detectors shows that such advanced receiver structures are quite sensitive to errors in phase and timing estimates. With parameter estimation errors the performance of all investigated detectors approach that of the conventional matched filter detector. This emphasizes even more the important role of channel coding in CDMA systems. A family of powerful very low-rate maximum free distance convolutional codes is found by nesting of rate 1/4 ODS codes. These codes are proposed for combined coding and spreading in CDMA systems, and are shown to be both more flexible and more powerful than previously known very low-rate convolutional codes. When applied in a CDMA system, we obtain significantly better performance than with a conventionally coded and spread scheme. Detailed investigations of parallel and successive interference cancellation in combination with channel code decoding show performance very close to the single user bound for the very low-rate code. All results with interference cancellation assume that decisions are taken before regeneration and subtraction of the signal. Accurate analysis of such non-linear interference cancellation is difficult. We therefore present iterative approximative analysis techniques that give results close to simulation results. Sequential decoding of convolutional codes is a suboptimum technique that makes it possible to decode very long constraint length codes and thus obtain very low error rates. We evaluate the performance of sequential decoding theoretically and by simulations for Rayleigh fading channels. A tailbiting coding scheme together with sequential decoding is proposed and shown to give improved throughput for wireless packet data transmission.
Pro-survival AKT and ERK signaling from EGFR and mutant EGFRvIII enhances DNA double-strand break repair in human glioma cells

The Epidermal growth factor receptor (EGFR) is frequently dysregulated in malignant glioma that leads to increased resistance to cancer therapy. Up-regulation of wild type or expression of mutants such as EGFR variant III (EGFRvIII), the most common EGFR mutation in malignant glioma, is associated with tumor radioresistance and poor clinical outcome. This radioresistance is thought to be the result of a strong cytoprotective response fueled by signaling via AKT and ERK that is heightened by radiation in the clinical dose range. Several groups including ours have shown that this response may modulate DNA repair. Herein, we show that expression of EGFRvIII promoted Pro-survival AKT and ERK signaling from EGFR and mutant EGFRvIII enhances DNA double-strand break repair in human glioma cells γ-H2AX foci resolution, a surrogate for double-strand break (DSB) repair, and thus enhanced DNA repair. Conversely, small molecule inhibitors targeting EGFR, MEK, and the expression of dominant-negative EGFR (EGFR-CD533) significantly reduced the resolution of γ-H2AX foci. When homologous recombination repair (HRR) and non-homologous end joining (NHEJ) were specifically examined, we found that EGFRvIII stimulated and CD533 compromised HRR and NHEJ, respectively. Furthermore, NHEJ was significantly blocked by inhibitors of AKT and ERK signaling pathways. Moreover, expression of EGFRvIII and CD533 increased and reduced, respectively, the formation of phospho-DNA-PKcs and -ATM repair foci, and RAD51 expression levels, indicating that DSB repair is regulated at multiple levels. Altogether, signaling from EGFR and EGFRvIII promotes both HRR and NHEJ that is likely one contributing factor towards the radioresistance of malignant gliomas.
Evaluation of multi-objective genetic algorithm for RoboCupSoccer team evolution

Researchers have applied genetic algorithm (GA) to RoboCupSoccer players/teams and evaluate the effectiveness of the algorithm in evolving good players and teams, but further investigations are required to know more about the ability of the algorithm. This paper reports our experience and findings on the application of multi-objective GA to the evolution of Robocup soccer teams: how well teams with various performances (e.g., offensive, defensive, balanced) can be automatically obtained by means of multi-objective GA.
Fusing Affective Dimensions and Audio-Visual Features from Segmented Video for Depression Recognition: INAOE-BUAP's Participation at AVEC'14 Challenge

Depression is a disease that affects a considerable portion of the world population. Severe cases of depression interfere with the common live of patients, for those patients a strict monitoring is necessary in order to control the progress of the disease and to prevent undesired side effects. A way to keep track of patients with depression is by means of online monitoring via human-computer-interaction. The AVEC'14 challenge aims at developing technology towards the online monitoring of depression patients. This paper describes an approach to depression recognition from audiovisual information in the context of the AVEC'14 challenge. The proposed method relies on an effective voice segmentation procedure, followed by segment-level feature extraction and aggregation. Finally, a meta-model is trained to fuse mono-modal information. The main novel features of our proposal are that (1) we use affective dimensions for building depression recognition models; (2) we extract visual information from voice and silence segments separately; (3) we consolidate features and use a meta-model for fusion. The proposed methodology is evaluated, experimental results reveal the method is competitive.
Investigating basal ganglia function using ultra-high field MRI

The basal ganglia (BG) are a group of highly interconnected nuclei that are located deep at the base of the cerebral cortex. They participate in multiple neural circuits or 'loops' with cognitive and motor areas of the cerebral cortex. The basal ganglia has primarily been thought to be involved in motor control and learning, but more recently a number of brain imaging studies have shown that the basal ganglia are involved also in cognitive function. The aim of this work is to investigate the role of the basal ganglia in cognitive control and motor learning by examining its involvement in GO/WAIT and GO/NO-GO tasks, and Motor Prediction task, respectively. Ultra-high field (7 Tesla) fMRI is used to provide higher BOLD contrast and thus higher achievable spatial resolution. A dual echo gradient echo EPI method is used to obtain high quality images from both cortical and sub-cortical regions. A common neural basis across different forms of response inhibition using GO/WAIT and GO/NO-GO cognitive paradigms is observed in the experiments of Chapter 4, as well as distinct brain regions involved in withholding and cancelling of motor responses. Using the GO/WAIT cognitive paradigm in Chapter 5 individuals with Tourette syndrome (TS) are compared to age and gender-matched control healthy subjects (CS), and it is shown that TS subjects are unable to recruit critical cortical and sub-cortical nodes that are typically involved in mediating behavioural inhibition. Furthermore, in Chapter 6, the role of the basal ganglia in motor learning is investigated using the Motor Prediction task. The findings show that the basal ganglia and midbrain regions (i.e., habenula) are involved in motor prediction and enhancing the reinforcement learning process. This thesis aims to investigate the basal ganglia function in cognitive and motor tasks, and concludes with suggested further studies to advance our understanding of the role of the basal ganglia nuclei in cognitive function.
Integrity and Change in Modular Ontologies

The benefits of modular representations arc well known from many areas of computer science. In this paper, we concentrate on the benefits of modular ontologies with respect to local containment of terminological reasoning. We define an architecture for modular ontologies that supports local reasoning by compiling implied subsumption relations. We further address the problem of guaranteeing the integrity of a modular ontology in the presence of local changes. We propose a strategy for analyzing changes and guiding the process of updating compiled information.
Partial Differential Postcorrelation Processing for GPS L2C Signal Acquisition

L2C is the second civilian signal introduced on the modernized block of GPS satellites. The two PRN sequences employed in L2C, named civil moderate (CM) and civil long (CL), have periods of 20 ms and 1.5 s, respectively. Stemming from the fact that using a full code period (CM or CL) for signal acquisition in GPS L2C receivers might not be necessary in normal situations (e.g. outdoor, light indoor, etc.), in this paper, we introduce a partial acquisition architecture using specially-designed matched filters (MFs) in order to relieve the computational complexity of the acquisition stage. The partial correlation loss is compensated by differential postcorrelation techniques. Three techniques, namely conventional differential combination (CDC), generalized differential combination (GDC), and modified generalized differential combination (MGDC), are investigated in terms of detection probabilities and mean acquisition time leading to the selection of MGDC as the most suitable technique for the L2C partial acquisition. By using this technique, a 2-dB sensitivity improvement with respect to the conventional noncoherent combination and a 94.5% reduction in mean acquisition time in comparison with the full code acquisition are shown for 1-ms partial correlation.
Ant Colony Optimisation for Stylometry: The Federalist Papers.

This paper describes the use of Ant Colony Optimisation for the classification of works of disputed authorship, in this case the Federalist Papers.Classification accuracy was 79.1%, which compares reasonably well with previous work on the same data set using neural networks and genetic algorithms. Although statistical approaches have performed much better than this, the advantage of a rule-based approach is the ability to produce readily intelligible criteria for the classification decisions made.
Efficacy of monitoring long‐bone fracture healing by measurement of either bone stiffness or resonant frequency: Numerical simulation

Development of noninvasive mechanical tests to monitor fracture healing has been hindered because relationships between bone geometry, measurement conditions, and fracture callus strength are not well understood. Beam theory was used to analyze the effects of fracture length, fracture location, end conditions, and fracture callus stiffness on mechanical properties (resonant frequency, bending stiffness, and torsional stiffness) of healing bone. Actual bone mineral geometry from a human tibia, quantified every 1 mm, was used in the beam analysis. Geometry of the fracture callus segment was uniformly scaled from the values for intact bone. Experimental tests on multisegmented machined rods were used to verify analytical methods. Mechanical properties of the healing bone initially increased very rapidly to 30–70% of the stiffness of intact bone, depending on the configuration. The increases then tapered off dramatically. Lateral bending stiffness was sensitive to changes in callus properties for a larger portion of the healing process than was either torsional stiffness or resonant frequency. Because callus strength increases at half the rate of callus stiffness, measures of whole‐bone mechanical properties can provide insight into changes in callus strength until a maximum of less than one‐half the strength of intact bone is regained. The analytical method presented is proposed for clinical use to develop individualized models of bone, fracture, and fixation conditions to identify early stages of healing. Because increases in whole‐bone mechanical properties are small in the later stages of fracture healing, however, such measures must be used prudently beyond the initial stages.