Miracle-dz/UniFAR-FTUs huggingface dataset:
Gender interactions in online debates: Look who's arguing with whom

This study identified patterns in gender interactions to explain observed gender differences in participation. Nineteen graduate students were randomly assigned to opposing teams to participate in five debates on a threaded discussion board. When posting messages to the debates, students labeled their own messages to identify each message by functional move associated with argumentation (e.g. argument, evidence, critique, elaboration). Computer programs were developed to apply the method of event sequence analysis to identify patterns in the gender interactions. The results showed that females were significantly less likely to engage in argumentation with other females than with males, providing one explanation for why females might post fewer messages than males. Males were equally likely to respond to females and males, with males showing a tendency to engage in more argumentative exchanges with other males than with females. The interactions that initiated the least to most discussion were female-to-female, male-tofemale, female-to-male, and male-to-male interactions, with male-to-male exchanges generating 36% more messages in discussion threads than female-to-female exchanges. These findings support Bakhtins dialogic theory (Koschmann, 1999) that underscores the importance of conflict in social interaction and the relationships between utterances that drive the processes of inquiry and discourse.
Radar frequency band invariant pedestrian classification

The problem of pedestrian classification by radars with different operating bands is considered. The proposed solutions are based on two observations of relation between Doppler spectrums collected within different frequency bands. According to the first observation the Doppler spectrum obtained from the radars with lower operating frequency is an approximate scaled version of the Doppler spectrum obtained within radar with higher operating frequency. According to the second observation the Doppler spectrum of lower operating frequency is similar to the Doppler spectrum of higher operating frequency at specific aspect angle. Two new approaches are proposed for pedestrian classification based on the observations. The first proposed approach deals with new features called local binary mask. The second approach is based on higher order spectral invariants estimated from the Doppler spectrum. The approaches are tested on real 24 GHz radar measurements and simulated 77 GHz radar measurements and show the robustness to operating frequency of the radar.
Self-concept clarity’s role in meaning in life among American college students: A latent growth approach‡

Abstract Meaning in life (MIL) is a fundamental building block of well-being, and MIL theory heavily emphasizes the importance of using self-knowledge to identify what makes life meaningful and to select suitable purposes to pursue in life. However, few studies have investigated this important theoretical point. The purpose of the present study was to investigate individual growth trajectories of self-knowledge, measured with a construct of self-concept clarity (SCC), and MIL. This study also examined whether the change of SCC predicts the change pattern of MIL using cross-domain latent growth analyses, controlling for the level of perceived stress. A longitudinal data-set with seventh measurement points was gathered from a total of 285 college students at a large Midwest university in the US during the period of 8 weeks. On average, a student’s levels of MIL and SCC tend to show a small amount of linear increase during the first semester of college, with individual differences in patterns of change. From a change perspective, SCC significantly predicted the sense of MIL, supporting the significance of having a clear self-view in perceiving life as more meaningful.
Secure Protocol for Incoming Sensor Node in the Dynamic Sensor Networks

The establishment of shared cryptography keys is one of the challenging problems in the sensor networks. Key Infection is a promising model to solve this problem on the commodity sensor networks without complex mechanism. This model, however, does not consider the mobility of sensors, so if sensor nodes move out of initial communication range, they cannot rejoin the network since they require new pair-wise key. Therefore, key infection model has been restricted in the static sensor network To be applied on the dynamic sensor networks, therefore, key infection model has to be extended to handle incoming sensor node. In this paper, we propose secure protocol for incoming sensor node in the dynamic sensor networks and verify the proposed protocol formally. Furthermore, we use simulation to investigate the effect of our proposed protocol.
Comparison of anti-EGFR-Fab’ conjugated immunoliposomes modified with two different conjugation linkers for siRNa delivery in SMMC-7721 cells

Background Targeted liposome-polycation-DNA complex (LPD), mainly conjugated with antibodies using functionalized PEG derivatives, is an effective nanovector for systemic delivery of small interference RNA (siRNA). However, there are few studies reporting the effect of different conjugation linkers on LPD for gene silencing. To clarify the influence of antibody conjugation linkers on LPD, we prepared two different immunoliposomes to deliver siRNA in which DSPE-PEG-COOH and DSPE-PEG-MAL, the commonly used PEG derivative linkers, were used to conjugate anti-EGFR Fab’ with the liposome. Methods First, 600 μg of anti-EGFR Fab’ was conjugated with 28.35 μL of a micelle solution containing DSPE-PEG-MAL or DSPE-PEG-COOH, and then post inserted into the prepared LPD. Various liposome parameters, including particle size, zeta potential, stability, and encapsulation efficiency were evaluated, and the targeting ability and gene silencing activity of TLPD-FPC (DSPE-PEG-COOH conjugated with Fab’) was compared with that of TLPD-FPM (DSPE-PEG-MAL conjugated with Fab’) in SMMC-7721 hepatocellular carcinoma cells. Results There was no significant difference in particle size between the two TLPDs, but the zeta potential was significantly different. Further, although there was no significant difference in siRNA encapsulation efficiency, cell viability, or serum stability between TLPD-FPM and TLPD-FPC, cellular uptake of TLPD-FPM was significantly greater than that of TLPD-FPC in EGFR-overexpressing SMMC-7721 cells. The luciferase gene silencing efficiency of TLPD-FPM was approximately three-fold high than that of TLPD-FPC. Conclusion Different conjugation linkers whereby antibodies are conjugated with LPD can affect the physicochemical properties of LPD and antibody conjugation efficiency, thus directly affecting the gene silencing effect of TLPD. Immunoliposomes prepared by DSPE-PEG-MAL conjugation with anti-EGFR Fab’ are more effective than TLPD containing DSPE-PEG-COOH in targeting hepatocellular carcinoma cells for siRNA delivery.
Development of an ultrasonic cane as a navigation aid for the blind people

The current study deals with the development of an ultrasonic based cane for the navigation of the blind persons. The developed cane is able to detect both aerial and ground obstacles and potholes (drop-off). The ultrasonic signals are acquired in the Arduino microcontroller, classified and control signals are generated. The control signals are transmitted wirelessly to the receiving device, kept in the shoulder pocket. The receiving device consists of another Arduino microcontroller which triggers 3 speaker panel (worn around the chest) and 3 LED panel. The device works in the range of 5-150 cm and may be used as a navigational aid for the blind persons.
Meta-Analysis of Primary Mesh Augmentation as Prophylactic Measure to Prevent Incisional Hernia

Background: Incisional hernia (IH) remains one of the most frequent postoperative complications after abdominal surgery. As a consequence, primary mesh augmentation (PMA), a technique to strengthen the abdominal wall, has been gaining popularity. This meta-analysis was conducted to evaluate the prophylactic effect of PMA on the incidence of IH compared to primary suture (PS). Methods: A meta-analysis was conducted according to the PRISMA guidelines. Randomized controlled trials (RCTs) comparing PMA and PS for closing the abdominal wall after surgery were included. Results: Out of 576 papers, 5 RCTs were selected comprising 346 patients. IH occurred significantly less in the PMA group (RR 0.25, 95% CI 0.12-0.52, I20%; p < 0.001). No difference could be observed with regard to wound infection (RR 0.86, 95% CI 0.39-1.91, I2 0%; p = 0.71) or seroma (RR 1.22, 95% CI 0.64-2.33, I2 0%; p = 0.55). A trend was observed for chronic pain in favor of the PS group (RR 5.95, 95% CI 0.74-48.03, I20%; p = 0.09). Conclusion: The use of PMA for abdominal wall closure is associated with significantly lower incidence of IH compared to PS.
A simple proof of Sklyanin's formula for canonical spectral coordinates of the rational Calogero-Moser system

We use Hamiltonian reduction to simplify Falqui and Mencattini's recent proof of Sklyanin's expression providing spectral Darboux coordinates of the rational Calogero-Moser system. This viewpoint enables us to verify a conjecture of Falqui and Mencattini, and to obtain Sklyanin's formula as a corollary.
EFFECT OF PRE-GERMINATION AND POST-GERMINATION TREATMENT WITH GROWTH HORMONES ( KINETINE AND ABSCISIC ACID ) ON ION CONCENTRATION AND BIOCHEMICAL CONTENTS OF FODDERBEET AND SEABEET UNDER SALINE CONDITIONS Banaras

In a pot experiment fodderbeet (Beta vulgaris sp. Majoral) and seabeet (Beta maritima) were grown under saline soil conditions. The seeds and seedlings were treated with kinetine and abscisic acid (10-6 M) to study the effect of hormones on the ion concentration (Na+, K+, Ca2+, Mg2+, Cl-) and biochemical relations (photosynthesis, sugar and glycinebetaine) in these plants. The concentration of Na+ increased with increasing salinity in the growth medium in the presence of the hormones. The Na:K ratio was lower in the roots than in the shoots. The concentration of Ca2+ was low in the presence of NaCl but treatment with the two hormones enhanced its uptake. The Ca:Mg ratio was lower in the roots than in the shoots. Seabeet had comparatively higher Ca:Mg ratio. The concentration of Clwas high in both species. NaCl enhanced the uptake of Clwhile kinetine and abscisic acid resisted it. Sugar content was increased in the presence of the two hormones. Pre-germination treatment with hormones enhanced sugar synthesis in fodderbeet while post-germination treatment showed a similar response in seabeet. Hormone treatment increased the glycinebetaine content in both species whereas no affect on net photosynthesis was observed. Differences in net photosynthesis were highly significant due only to different species. Reclamation of salt affected soils involves tremendous expenses for the re-
Recognizing slow eye movement for driver fatigue detection with machine learning approach

Slow eye movement (SEM) regarded as a sign of onset of sleep is very significant for detecting driver fatigue, but its characteristics and detection algorithm have been rarely involved in the study of driver fatigue detection. In this study, some new features were extracted based on wavelet singularity analysis and statistics to detect SEMs. Six subjects participated in this simulated driving experiment, and for each subject, a more than 2 hours electro-oculogram (EOG) session was recorded. Each session was divided into SEM epochs and non-SEM epochs according to the common judgments made by the two of three experts by the visual recognition criteria of SEMs. Regarding the problem of detecting SEMs as an imbalance classification problem, and through the under-sampling and over-sampling methods a 2s horizontal electro-oculogram (HEO) signal could finally be recognized as the category of SEMs or non-SEMs with the classifiers SVM, GELM, and KNN respectively. Results prove that the proposed features was a little better than the wavelet energy features, and through the combination of the wavelet energy features and the new features based on wavelet singularity analysis and statistics, the classification results were improved obviously.
Towards robust model selection using estimation and approximation error bounds

One of the main problems in machine learning and statistical inference is selecting an appropriate model by which a set of data can be explained. In the absense of any structured prior information aa to the data generating mechanism, one is often forced to consider a range of models, attempting to select the model which best explains the data, based on some quality criterion. While there have been many proposals for various criteria for model selection, most of these approaches suffer from some form of bias built into the construction of the criterion. Moreover, many of the standard methods are only guaranteed to work well asymptotically, leaving their behavior in the face of a finite amount of data completely unknown. In this paper we extend on previous work [17] and introduce a novel model selection criterion, based on combining two recent chains of thought. In particular we make use of the powerful framework of uniform convergence of empirical processes pioneered by Vapnik and Chernovenkins [23], combined with recent results concerning the approximation ability of non-linear manifolds of functions, focusing in particular on feedforward neural networks. The main contributions of this work are twofold: (i) Conceptual elucidating a coherent and robust framework for model selection, (ii) Technical the main contribution here is a lower bound on the approximation error (Theorem 10), which holds in a well specified sense for most functions of interest. As far as we are aware, this result is new in the field of function approximation.
Selection and Characterization of a Candidate Therapeutic Bacteriophage That Lyses the Escherichia coli O104:H4 Strain from the 2011 Outbreak in Germany

In 2011, a novel strain of O104:H4 Escherichia coli caused a serious outbreak of foodborne hemolytic uremic syndrome and bloody diarrhea in Germany. Antibiotics were of questionable use and 54 deaths occurred. Candidate therapeutic bacteriophages that efficiently lyse the E. coli O104:H4 outbreak strain could be selected rather easily from a phage bank or isolated from the environment. It is argued that phage therapy should be more considered as a potential armament against the growing threat of (resistant) bacterial infections.
Burnout as a Mediator Between Work–School Conflict and Work Outcomes

Conflict occurring between the roles of work and family has been heavily researched. Recently, however, research has been branching out to study roles beyond work and family. For example, a few researchers have investigated conflict that occurs between the roles of work and school. However, these studies have focused mainly on school and personal outcomes. As such, the present study seeks to contribute to the literature on work–school conflict in two main ways. First, we investigate the relationship between work–school conflict and job outcome variables. Next, we seek to understand the mediating mechanism through which work–school conflict affects job outcomes. Participants in this study were 304 students who completed a survey regarding their attitudes toward work and school. Results were largely supportive of the hypotheses predicting that work–school conflict predicted work outcomes and that burnout mediated these outcomes. Implications for organizations and universities are discussed.
Neuropathic pain: evidence matters

‘He slept less and less; they gave him opium and began to inject morphine. But this did not relieve him. The dull pain he experienced in the half asleep condition at first only relieved him as a change, but then it became as bad, or even more agonizing, than the open pain. ’
Automatic index creation for handwritten notes

This paper describes a technique for automatically creating an index for handwritten notes captured as digital ink. No text recognition is performed. Rather, a dictionary of possible index terms is built by clustering groups of ink strokes corresponding roughly to words. Terms whose distribution varies significantly across note pages are selected for the index. An index page containing the index terms is created, and terms are hyper-linked back to their original location in the notes. Further, index terms occurring in a note page are highlighted to aid browsing.
A unified approach to the analysis of radial waveguides, dielectric resonators, and microstrip antennas on spherical multilayer structures

This paper presents a uniform procedure to analyze radial waveguides, dielectric resonators, dielectric resonator antennas, and microstrip antennas on spherical structures. It can be applied to any type of spherical multilayer closed and sector structures, which also include hemispherical structures. The arbitrary layers may be airgaps or dielectric substrates with or without metallizations in the interfaces. The inner layer can be a metallic or dielectric core. The kernel of this approach is the derivation of the spectral- and space-domain dyadic Green's function of multilayer spherical structures by using an equivalent circuit and simple network analysis techniques. The relations between the spectral and space domains are derived using the vector-Legendre transformation. For the demonstration of the applicability of this approach, the dyadic Green's functions and the system equations of some commonly used spherical structures are presented, among which the system equation of a two-layer dielectric resonator is verified analytically with the literature. As an example, the resonant frequencies of a spherical resonator with two dielectric layers covering a metallic inner layer are calculated and verified with commercial software.
Targeting Antibody Responses to the Membrane Proximal External Region of the Envelope Glycoprotein of Human Immunodeficiency Virus

Although human immunodeficiency type 1 (HIV-1) infection induces strong antibody responses to the viral envelope glycoprotein (Env) only a few of these antibodies possess the capacity to neutralize a broad range of strains. The induction of such antibodies represents an important goal in the development of a preventive vaccine against the infection. Among the broadly neutralizing monoclonal antibodies discovered so far, three (2F5, Z13 and 4E10) target the short and hidden membrane proximal external region (MPER) of the gp41 transmembrane protein. Antibody responses to MPER are rarely observed in HIV-infected individuals or after immunization with Env immunogens. To initiate antibody responses to MPER in its membrane-embedded native conformation, we generated expression plasmids encoding the membrane-anchored ectodomain of gp41 with N-terminal deletions of various sizes. Following transfection of these plasmids, the MPER domains are displayed on the cell surface and incorporated into HIV virus like particles (VLP). Transfected cells displaying MPER mutants bound as efficiently to both 2F5 and 4E10 as cells transfected with a plasmid encoding full-length Env. Mice immunized with VLPs containing the MPER mutants produced MPER-specific antibodies, the levels of which could be increased by the trimerization of the displayed proteins as well as by a DNA prime-VLP boost immunization strategy. Although 2F5 competed for binding to MPER with antibodies in sera of some of the immunized mice, neutralizing activity could not be detected. Whether this is due to inefficient binding of the induced antibodies to MPER in the context of wild type Env or whether the overall MPER-specific antibody response induced by the MPER display mutants is too low to reveal neutralizing activity, remains to be determined.
Performance improvements to the BBN Byblos OCR system

In this paper, we describe four recent enhancements to the BBN Byblos OCR system, a multilingual HMM-based character recognition system which has been demonstrated on a variety of languages, including English, Arabic, Chinese, and Japanese. These enhancements are implemented as optional extensions to the system and provide improved performance for certain scripts or domains. Projection-based re-estimation of line boundaries reduces instability in the presence of some types of noise. An alternate modeling strategy used in the first of two recognition search passes substantially increases speed on languages with a large number of characters. Another speed improvement comes from automatic discovery and modeling of sub-characters. The use of heteroschedastic linear discriminant analysis (HLDA) makes modeling more tractable by reducing feature-space dimensionality.
A Modelling the Thermal Dynamics of Buildings: A Latent Force Model Based Approach

Minimizing the energy consumed on heating, ventilation and air conditioning (HVAC) systems of residential buildings, without impacting occupants’ comfort has been highlighted as an important artificial intelligence (AI) challenge. Typically, approaches that seek to address this challenge use a model that captures the thermal dynamics within a building, also referred to as a thermal model. Amongst thermal models, greybox models are a popular choice for modelling the thermal dynamics of buildings. They combine knowledge of the physical structure of a building with various data-driven inputs, and are accurate estimators of the state (internal temperature). However, existing grey-box models require a detailed specification of all the physical elements that can affect the thermal dynamics of a building a priori. This limits their applicability, particularly in residential buildings, where additional dynamics can be induced by human activities such as cooking, which contributes additional heat, or opening of windows that leads to additional leakage of heat. Since the incidence of these additional dynamics is rarely known, their combined effects cannot readily be accommodated within existing models. To overcome this limitation and improve the general applicability of grey-box models, we introduce a novel model, which we refer to as a latent force thermal model of the thermal dynamics of a building or LFM-TM. Our model is derived from an existing grey-box thermal model, which is augmented with an extra term referred to as the learned residual. This term is capable of modelling the effect of any a priori unknown additional dynamic, which if not captured, appears as structure in a thermal models residual (the error induced by the model). More importantly, the learned residual can also capture the effects of physical elements such as a building’s envelope or the lags in a heating system, leading to a significant reduction in complexity compared to existing models. To evaluate the performance of LFM-TM, we apply it to two independent data sources. The first is an established dataset, referred to as the FlexHouse data, which was previously used for evaluating the efficacy of existing grey-box models [Bacher and Madsen 2011]. The second dataset consists of heating data logged within homes located on University of Southampton campus, which were specifically instrumented to collect data for our thermal modelling experiments. On both datasets, we show that LFM-TM outperforms existing models in its ability to accurately fit the observed data, generate accurate day-ahead internal temperature predictions and explain a large amount of the variability in the future observations. This, along with the fact that we also use a corresponding efficient sequential inference scheme for LFM-TM, makes it an ideal candidate for model-based predictive control, where having accurate online predictions of internal temperatures, is essential for high quality solutions.