Miracle-dz/UniFAR-FTUs huggingface dataset:
Introducing the Geneva Multimodal Emotion Portrayal (GEMEP) corpus

In this chapter we outline the requirements for a systematic corpus of actor portrayals and describe the development, recording, editing, and validating of a major new corpus, the Geneva Multimodal Emotion Portrayal (GEMEP). This corpus consists of more than 7,000 audio-video emotion portrayals, representing 18 emotions (including rarely studied subtle emotions), portrayed by 10 professional actors who were coached by a professional director. The portrayals are recorded with optimal digital quality in multiple modalities, using both pseudo linguistic utterances and affect bursts. In addition, the corpus includes stimuli with systematically varied intensity levels, as well as instances of masked expressions. From the total corpus, 1,260 portrayals were selected and submitted to a first rating procedure in different modalities to establish validity in terms of inter-judge reliability and recognition accuracy. The results show that the portrayed expressions are recognized by lay judges with an accuracy level that, in the case of all emotions, largely exceeded chance and that compares very favorably with published tests of emotion recognition that use highly selected stimulus sets. The portrayals also reach very satisfactory levels of inter-rater reliability for category judgments and ratings of believability and intensity of the portrayals. The validity of the corpus is further confirmed by replicating results in earlier work on the role of expression modality and the corresponding communication channel for cue utilization in emotion recognition. We show that, as expected, the highest accuracy results if both auditory and visual information (voice, face, and gestures) is available, but that sizeable accuracy is achieved even when only one modality is available. The video modality is slightly superior to the audio modality, probably reflecting the fact that facial and gestural cues are more discrete and iconic than vocal cues. However, there are important interactions between emotion and modality, as particular emotions seem to be preferentially communicated by visual or audio cues. The results also raise important issues concerning the relationships
An adaptive neurocontroller using RBFN for robot manipulators

In recent years, neural networks have fulfilled the promise of providing model-free learning controllers for nonlinear systems; however, it is very difficult to guarantee the stability and robustness of neural network control systems. This paper proposes an adaptive neurocontroller for robot manipulators based on the radial basis function network (RBFN). The RBFN is a branch of neural networks and is mathematically tractable. Therefore, we adopt the RBFN to approximate nonlinear robot dynamics. The RBFN generates control input signals based on the Lyapunov stability that is often used in the conventional control schemes. A saturation function is also chosen as an auxiliary controller to guarantee the stability and robustness of the control system under the external disturbances and modeling uncertainties.
alaria control under unstable dynamics : Reactive vs . climate-based trategies

In areas of the world where malaria prevails under unstable conditions, attacking the adult vector population through insecticide-based Indoor Residual Spraying (IRS) is the most common method for controlling epidemics. Defined in policy guidance, the use of Annual Parasitic Incidence (API) is an important tool for assessing the effectiveness of control and for planning new interventions. To investigate the consequences that a policy based on API in previous seasons might have on the population dynamics of the disease and on control itself in regions of low and seasonal transmission, we formulate a mathematical malaria model that couples epidemiologic and vector dynamics with IRS intervention. This model is parameterized for a low transmission and semi-arid region in northwest India, where epidemics are driven by high rainfall variability. We show that this type of feedback mechanism in control strategies can generate transient cycles in malaria even in the absence of environmental variability, and that this tendency to cycle can in turn limit the effectiveness of control in the presence of such variability. Specifically, for realistic rainfall conditions and over a range of control intensities, the effectiveness of such ‘reactive’ intervention is compared to that of an alternative strategy based on rainfall and therefore vector variabilrid environments lasmodium falciparum malaria alaria elimination ity. Results show that the efficacy of intervention is strongly influenced by rainfall variability and the type of policy implemented. In particular, under an API ‘reactive’ policy, high vector populations can coincide more frequently with low control coverage, and in so doing generate large unexpected epidemics and decrease the likelihood of elimination. These results highlight the importance of incorporating information on climate variability, rather than previous incidence, in planning IRS interventions in regions of unstable malaria. These findings are discussed in the more general context of elimination and other low transmission regions such as highlands.
In Silico Approach for Predicting Toxicity of Peptides and Proteins

Background Over the past few decades, scientific research has been focused on developing peptide/protein-based therapies to treat various diseases. With the several advantages over small molecules, including high specificity, high penetration, ease of manufacturing, peptides have emerged as promising therapeutic molecules against many diseases. However, one of the bottlenecks in peptide/protein-based therapy is their toxicity. Therefore, in the present study, we developed in silico models for predicting toxicity of peptides and proteins. Description We obtained toxic peptides having 35 or fewer residues from various databases for developing prediction models. Non-toxic or random peptides were obtained from SwissProt and TrEMBL. It was observed that certain residues like Cys, His, Asn, and Pro are abundant as well as preferred at various positions in toxic peptides. We developed models based on machine learning technique and quantitative matrix using various properties of peptides for predicting toxicity of peptides. The performance of dipeptide-based model in terms of accuracy was 94.50% with MCC 0.88. In addition, various motifs were extracted from the toxic peptides and this information was combined with dipeptide-based model for developing a hybrid model. In order to evaluate the over-optimization of the best model based on dipeptide composition, we evaluated its performance on independent datasets and achieved accuracy around 90%. Based on above study, a web server, ToxinPred has been developed, which would be helpful in predicting (i) toxicity or non-toxicity of peptides, (ii) minimum mutations in peptides for increasing or decreasing their toxicity, and (iii) toxic regions in proteins. Conclusion ToxinPred is a unique in silico method of its kind, which will be useful in predicting toxicity of peptides/proteins. In addition, it will be useful in designing least toxic peptides and discovering toxic regions in proteins. We hope that the development of ToxinPred will provide momentum to peptide/protein-based drug discovery (http://crdd.osdd.net/raghava/toxinpred/).
Performance Impacts of Big Data Analytics

Big Data Analytics has been a ‘hot topic’ for industry and academic during the past few years. This paper examines what constitutes Big Data Analytics (BDA) and how it relates to organizational performance. It also investigates what other factors influence this relationship, whether BDA leads to more data-driven decision-making (DDDM) and whether the latter is really superior to less informed decision-making. The study first operationalizes Big Data Analytics, and then develops a research model which manifests the direct and indirect relationships between analytic capability, DDDM, and organizational performance.
Toward a Collaborative Approach to Parent Involvement in Early Education: A Study of Teenage Mothers in an African-American Community

This study addresses the challenge of creating a collaborative approach to parent involvement. As part of a family literacy program, participants in the study were 19 African-American adolescent parents from low-income backgrounds whose children attended an early intervention program. Parents’ beliefs about learning and literacy were sought through a series of peer group discussions. The data revealed a continuum of perspectives ranging from behavioral to constructivist beliefs, suggesting important intragroup variability within this particular sociocultural group. The discussions also revealed shared goals that may be used to forge collaborative relationships between parents and professionals in the interest of improving African-American children’s early education. Illustrations from a family literacy program are used to show how parent beliefs may be incorporated into programmatic changes, building constructive relationships that work toward supporting children’s success in schools.
A fold for all seasons

Generic control operators, such as fold,, can be generated from algebraic type definitions. The class of types to which these techniques are applicable is generalized to all algebraic types definable in languages such as Miranda and ML, i.e. mutually recursive sums-of-products with tuplee and function types. Several other useful generic operators, aleo applicable to every type in thw class, also are described. A normalization algorithm which automatically calculates improvements to programs expressed in a language baaed upon folds is described. It rednces programs, expressed using fold sz the exclusive control operator, to a canonical form. Based upon a generic promotion theorem, the algorithm is facilitated by the explicit structure of fold programs rather than using an analysis phase to search for implicit structure. Canonical programs are minimal in the sense that they contain the fewest number of fold operations. Because of this property, the normalization algorithm haa important applications in program transformation, optimization, and theorem proving. In addition a generic promotion theorem ia identified for each of the other operators. It is hoped that these theorems can be the basis of normalization algorithms for the other operators as well.
Allopurinol Enhances the Contractile Response to Dobutamine and Exercise in Dogs With Pacing-Induced Heart Failure

Background —Superoxide (O2−) generated by enhanced xanthine oxidase (XO) activity may contribute to the increased myocardial oxidative stress in heart failure (CHF). Because blocking XO with allopurinol augments myofilament Ca2+ sensitivity in reperfusion injury and CHF, we hypothesized that it may improve adrenergic inotropic responsiveness in CHF. Methods and Results —We studied the effect of allopurinol on the contractile response to dobutamine and exercise in 7 chronically instrumented conscious dogs before and after producing CHF by rapid pacing. Left ventricular (LV) contractile performance was measured by the slopes of the LV end-systolic pressure-volume relation (EES) and stroke work–end-diastolic volume relation (MSW). Before CHF, allopurinol produced no change in LV contractile performance and did not alter the response to dobutamine or exercise. After CHF, allopurinol produced significant (P <0.05) increases in EES (5.0±0.6 versus 3.3±0.6 mm Hg/mL) and MSW. Dobutamine and allopurinol produced greater increases in EES (5.4±0.6 versus 7.4±0.6 mm Hg/mL) and MSW (60.1±7.4 versus 73.7±4.4 mm Hg) than did dobutamine alone. After allopurinol, dP/dtmax, stroke volume, and MSW were higher during CHF exercise. LV diastolic pressures were lower during CHF exercise after allopurinol. Conclusions —Allopurinol has no discernable effects on LV contractile function or adrenergic responsiveness in normal, conscious animals. In pacing-induced CHF, however, allopurinol improves LV systolic function at rest and during adrenergic stimulation and exercise.
Adaptive Strategies in Peasant Agricultural Production

Considerable social science research has been carried out in recent years on agricultural change among peasant farmers in developing countries. This research has been noteworthy for two reasons. On the one hand, there is a trend toward joining the approaches of economic anthropology and cul­ tural ecology in the study of production processes in peasant communities. In many cases, this combination of approaches transcends the substantivist­ formalist controversy of the 19608 and moves the focus of research toward adaptive strategies and the integration of individual decisions and commu­ nity patterns. Second, research on agricultural production relates more directly than many areas of anthropology to current issues of global concern and provides relevant data to practitioners as well as to academics. With an increasing awareness of worldwide inequalities in the distribution of food and produc­ tive resources and of food shortages in some countries, attention has turned to the small farmers of the world, whose lands employ the majority of the world's people, but whose productivity is being rapidly outstripped by recent increases in population. The failure of the "development decade" of the 19608 to ameliorate these conditions or to improve standards of living in most rural areas has led to a greater concern, both within international development agencies and within national governments, to understand the agricultural decisions of these peasant farmers.
Criteria for chaos synchronization of a class of Lurie systems

This paper addresses the synchronization control between Lurie chaotic systems by means of LMI. moreover, synchronization between the time-delay systems has been investigated. By the method of LMI, the control function is designed and the parameterpsilas range is obtained when the two time-delay systems are synchronous. Numerical simulations by Matlab indicate the feasibility of the method. Furthermore, the results demonstrate the effectiveness of the proposed chaos synchronization scheme.
Internet of Things: Security challenges for next generation networks

Internet of Things(IoT) is the next big boom in the networking field. The vision of IoT is to connect daily used objects (which have the ability of sensing and actuation) to the Internet. This may or may or may not involve human. IoT field is still maturing and has many open issues. We build up on the security issues. As the devices have low computational power and low memory the existing security mechanisms (which are a necessity) should also be optimized accordingly or a clean slate approach needs to be followed. This is a survey paper to focus on the security aspects of IoT. We further also discuss the open challenges in this field.
“No no no” and Other Types of Multiple Sayings in Social Interaction

Relying on the methodology of conversation analysis, this article examines a practice in ordinary conversation characterized by the resaying of a word, phrase, or sentence. The article shows that multiple sayings such as “No no no” or “Alright alright alright” are systematic in both their positioning relative to the interlocutor’s talk and in their function. Specifically, the findings are that multiple sayings are a resource speakers have to display that their turn is addressing an in progress course of action rather than only the just prior utterance. Speakers of multiple sayings communicate their stance that the prior speaker has persisted unnecessarily in the prior course of action and should properly halt course of action.
Investigation of the ESD induced clock disturbances in portable electronic products

ESD events can induce noise on the system clock which may lead to soft-errors in the portable electronic products. This paper presents measurement techniques to investigate the ESD induced clock disturbances. At first, the soft-errors due to system level ESD testing on a DUT are shown. Next, local field scanning and direct injection are performed to identify ESD sensitive areas/traces. Techniques for soft-error threshold measurement using synchronized noise injection techniques are shown. Short time FFT (STFFT) based spectrogram method to investigate the PLL output frequency deviation due to the clock line noise, is presented.
Capacity Region of the Asynchronous Gaussian Vector Multiple-Access Channel

In this paper, we derive explicit expressions for the capacity region of the two-user symbol-asynchronous Gaussian vector multiple-access channel. Verdú considered the case where each user linearly modulates a fixed waveform in each symbol period, where the symbol periods for the users are not perfectly aligned at the receiver. He derived explicit capacity region expressions for the case where the transmitters have knowledge of the mutual offset and also for the case where the transmitters have no knowledge of the mutual offset. In this paper, we extend Verdú's results to allow each user to linearly modulate a set of orthonormal waveforms, instead of a single waveform, in each symbol period and with no restrictions imposed on the waveforms. We consider group power constraints, which include individual sum power constraints, as orthonormal waveforms assigned to each user may come from different frequency bands with different power constraints. Similar to the case where each user is allowed to linearly modulate only a single waveform, our results hold regardless of whether or not the transmitters are frame synchronous. In addition, we present some results that are necessary to numerically compute the capacity region expressions with general purpose convex optimization algorithms. Next, we simplify the capacity region expression when there are only individual sum power constraints and when the transmitters know the mutual offset. We also prove a sufficient condition for a similar simplification to hold when the transmitters have no knowledge of the mutual offset. Finally, we consider a specialized algorithm to numerically compute the simplified capacity region expression when the transmitters know the mutual offset.
Bcl-2 Inhibitors: Targeting Mitochondrial Apoptotic Pathways in Cancer Therapy

Defects in apoptotic pathways can promote cancer cell survival and also confer resistance to antineoplastic drugs. One pathway being targeted for antineoplastic therapy is the anti-apoptotic B-cell lymphoma-2 (Bcl-2) family of proteins (Bcl-2, Bcl-XL, Bcl-w, Mcl-1, Bfl1/A-1, and Bcl-B) that bind to and inactivate BH3-domain pro-apoptotic proteins. Signals transmitted by cellular damage (including antineoplastic drugs) or cytokine deprivation can initiate apoptosis via the intrinsic apoptotic pathway. It is controversial whether some BH3-domain proteins (Bim or tBid) directly activate multidomain pro-apoptotic proteins (e.g., Bax and Bak) or act via inhibition of those anti-apoptotic Bcl-2 proteins (Bcl-2, Bcl-XL, Bcl-w, Mcl-1, Bfl1/A-1, and Bcl-B) that stabilize pro-apoptotic proteins. Overexpression of anti-apoptotic Bcl-2 family members has been associated with chemotherapy resistance in various human cancers, and preclinical studies have shown that agents targeting anti-apoptotic Bcl-2 family members have preclinical activity as single agents and in combination with other antineoplastic agents. Clinical trials of several investigational drugs targeting the Bcl-2 family (oblimersen sodium, AT-101, ABT-263, GX15-070) are ongoing. Here, we review the role of the Bcl-2 family in apoptotic pathways and those agents that are known and/or designed to inhibit the anti-apoptotic Bcl-2 family of proteins.
Application of Metacognitive Strategy Training into Listening Class

Metacognitive strategies involve thinking and actions learners use to control or regulate their cognition in learning process. In China, foreign language teaching still has a long way to go in transforming from the “teachercentered” model to “learner-centered” model, because college students lack knowledge to control their learning. The research carried out metacognitive strategy training on a group of non-English majors in listening class in Shenyang Ligong University and investigated the effectiveness of the training.
The number system hidden inside the Boolean satisfiability problem

This paper gives a novel approach to analyze SAT problem more deeply. First, I define new elements of Boolean formula such as dominant variable, decision chain, and chain coupler. Through the analysis of the SAT problem using the elements, I prove that we can construct a k-SAT (k>2) instance where the coefficients of cutting planes take exponentially large values in the input size. This exponential property is caused by the number system formed from the calculation of coefficients. In addition, I show that 2-SAT does not form the number system and Horn-SAT partially forms the number system according to the feasible value of the dominant variable. Whether or not the coefficients of cutting planes in cutting plane proof are polynomially bounded was open problem. Many researchers believed that cutting plane proofs with large coefficients are highly non-intuitive20. However, we can construct a k-SAT (k>2) instance in which cutting planes take exponentially large coefficients by the number system. In addition, this exponential property is so strong that it gives definite answers for several questions: why Horn-SAT has the intermediate property between 2-SAT and 3-SAT; why random-SAT is so easy; and why k-SAT (k>2) cannot be solved with the linear programming technique. As we know, 2-SAT is NL-complete, Horn-SAT is P-complete, and k-SAT (k>2) is NP-complete. In terms of computational complexity, this paper gives a clear mathematical property by which SAT problems in three different classes are distinguished.
Emotional intelligence and human relationship management as predictors of organizational commitment

The study seeks to explain the interactive and relative effects of emotional intelligence and human relationship management on the organizational commitment of Nigerian civil servants . Simple random sampling technique was used in selecting 300 participants from Ministries of Education, Local government affairs, Civil service commission, Agriculture and Governors office of Bayelsa and Oyo States. Of the sample selected, 160 were males and 140 were females. Their ages range between 28 and 55 years with a mean age of 36.7 and a standard deviation of 6.9. Three instruments: Emotional intelligence scales (EIS), Human relationship management scale (HRMS) and Organizational commitment questionnaire (OCQ) were used to collect data from the participants. Data analysis involved the use of Pearson Product Moment Correlation and multiple regressions. The results indicated that the two independent variables, when taken together, were effective in predicting organizational commitment. Each of the variables contributed significantly to the prediction of organizational commitment with emotional intelligence making higher contribution to the prediction of Organizational commitment. Based on the outcome of the study, Emotional intelligence intervention and Human relationship management programmes were advocated in order to enhance the organizational commitment of the civil servants.
Relational-interdependent self-construal

Relational-interdependent self-construal (RISC) refers to the tendency to think of oneself in terms of close relationships. We examined how self-construal predicted cognitions and affect within friendships. When listing friends, individuals named friends whom they perceived to be similar to the self in RISC (Study 1), but this was not because it was harder to think of perceived dissimilar friends (Studies 1 and 2). However, perceptions of the friend’s RISC did not match the friend’s self-rating (Study 3). In regards to affect, all individuals reported higher friendship quality with perceived high RISC friends. These findings support the similarity-attraction hypothesis for individuals high in RISC. However, for individuals low in RISC, it is dissimilarity (i.e., high RISC friend) that predicts friendship quality.