Miracle-dz/UniFAR-FTUs huggingface dataset:
Potential chemotherapeutic targets for Japanese encephalitis: current status of antiviral drug development and future challenges

Introduction: Japanese encephalitis (JE) remains a public health threat in Asia. Although several vaccines have been licensed, ∼ 67,900 cases of the disease are estimated to occur annually, probably because the vaccine coverage is low. Therefore, effective antiviral drugs are required to control JE. However, no licensed anti-JE drugs are available, despite extensive efforts to develop them. Areas covered: We provide a general overview of JE and JE virus, including its transmission cycle, distribution, structure, replication machinery, immune evasion mechanisms and vaccines. The current situation in antiviral drug development is then reviewed and future perspectives are discussed. Expert opinion: Although the development of effective anti-JE drugs is an urgent issue, only supportive care is currently available. Recent progress in our understanding of the viral replication machinery and immune evasion strategies has identified new targets for anti-JE drug development. To date, most candidate drugs have only been evaluated in single-drug formulations, and efficient drug delivery to the CNS has virtually not been considered. However, an effective anti-JE treatment is expected to be achieved with multiple-drug formulations and a targeted drug delivery system in the near future.
Mathematics Knowledge for Teaching: Questions about Constructs

I propose that a single construct underlies all the measures described in this series of studies, and that construct is deep knowledge of mathematics, not a mathematics different from that known by mathematicians or mathematically competent adults, and not a superficial understanding of algorithms that is often the outcome of students’ learning in the current system of mathematics education. Knowledge of students and pedagogical techniques may also be important, but the study described in these articles does not address the importance of pedagogical techniques. Knowledge of students and pedagogy must be built on a foundation of deep understanding of mathematics which is not algorithmic prowess, but an ability to communicate mathematically, represent mathematics in different forms, and engage in problem-solving and reasoning mathematically.
Cyclic pursuit formation control for arbitrary desired shapes

A multi-agent system comprises numerous agents that autonomously make decisions to collectively accomplish tasks, drawing significant attention for their wide-ranging applications. Within this context, formation control emerges as a prominent task, wherein agents collaboratively shape and maneuver while preserving formation integrity. Our focus centers on cyclic pursuit, a method facilitating the formation of circles, ellipses, and figure-eights under the assumption that agents can only perceive the relative positions of those preceding them. However, this method's scope has been restricted to these specific shapes, leaving the feasibility of forming other shapes uncertain. In response, our study proposes a novel method based on cyclic pursuit capable of forming a broader array of shapes, enabling agents to individually shape while pursuing preceding agents, thereby extending the repertoire of achievable formations. We present two scenarios concerning the information available to agents and devise formation control methods tailored to each scenario. Through extensive simulations, we demonstrate the efficacy of our proposed method in forming multiple shapes, including those represented as Fourier series, thereby underscoring the versatility and effectiveness of our approach.
Optimization of Medium Compositions Using Statistical Experimental Design to Produce Lipase by Bacillus subtilis

Statistical experimental design was employed to optimize medium compositions to enhance the activity of lipase from Bacillus subtilis. Plackett–Burman design was applied to evaluate the effect of different medium compositions obtained by one-factor-at-a-time experiments, and ammonium chloride, ammonium sulfate and dipotassium hydrogen phosphate were found to influence the activity of lipase significantly. Steepest ascent method was employed to approach the experimental design space, followed by an application of central composite design and response surface methodology for further optimization. A quadratic model was found to fit the lipase activity, and the optimal medium compositions were determined as included 45 g L NH4Cl, 20.4 g L –1 (NH4)2SO4 and 12.6 g L K2HPO4. The corresponding lipase activity was 91.39 U mL . Validation experiments were also carried out to prove the adequacy and the accuracy of the model obtained. The lipase activity reached 91.46 U mL, which was almost equal to the actual predicted value, about 4.94-fold increase compared with that using the original medium.
Protein pathway and complex clustering of correlated mRNA and protein expression analyses in Saccharomyces cerevisiae

The mRNA and protein expression in Saccharomyces cerevisiae cultured in rich or minimal media was analyzed by oligonucleotide arrays and quantitative multidimensional protein identification technology. The overall correlation between mRNA and protein expression was weakly positive with a Spearman rank correlation coefficient of 0.45 for 678 loci. To place the data sets in a proper biological context, a clustering approach based on protein pathways and protein complexes was implemented. Protein expression levels were transcriptionally controlled for not only single loci but for entire protein pathways (e.g., Met, Arg, and Leu biosynthetic pathways). In contrast, the protein expression of loci in several protein complexes (e.g., SPT, COPI, and ribosome) was posttranscriptionally controlled. The coupling of the methods described provided insight into the biology of S. cerevisiae and a clustering strategy by which future studies should be based.
Functional MRI cerebral activation and deactivation during finger movement

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The cloudier side of cryptographic end-to-end verifiable voting: a security analysis of Helios

Helios is an open-audit internet voting system providing cryptographic protections to voter privacy, and election integrity. As part of these protections, Helios produces a cryptographic audit trail that can be used to verify ballots were correctly counted. Cryptographic end-to-end (E2E) election verification schemes of this kind are a promising step toward developing trustworthy electronic voting systems. In this paper we approach the discussion from the flip-side by exploring the practical potential for threats to be introduced by the presence of a cryptographic audit trail. We conducted a security analysis of the Helios implementation and discovered a range of vulnerabilities and implemented exploits that would: allow a malicious election official to produce arbitrary election results with accepting proofs of correctness; allow a malicious voter to cast a malformed ballot to prevent the tally from being computed; and, allow an attacker to surreptitiously cast a ballot on a voter's behalf. We also examine privacy issues including a random-number generation bias affecting the indistinguishably of encrypted ballots. We reported the issues and worked with the Helios designers to fix them.
Scaling up multiphoton neural scanning: The SSA algorithm

In order to reverse-engineer the information processing capabilities of the cortical circuit, we need to densely sample neural circuit; it may be necessary to sample the activity of thousands of neurons simultaneously. Frame scanning techniques do not scale well in this regard, due to the time ”wasted” scanning extracellular space. For scanners in which inertia can be neglected, path length minimization strategies enable large populations to be imaged at relatively high sampling rates. However, in a standard multiphoton microscope, the scanners responsible for beam deflection are inertial, indicating that an optimal solution should take rotor and mirror momentum into account. We therefore characterized the galvanometric scanners of a commercial multiphoton microscope, in order to develop and validate a MATLAB model of microscope scanning dynamics. We tested the model by simulating scan paths across pseudo-randomly positioned neuronal populations of differing neuronal density and field of view. This model motivated the development of a novel scanning algorithm, Adaptive Spiral Scanning (SSA), in which the radius of a circular trajectory is constantly updated such that it follows a spiral trajectory scanning all the cells. Due to the kinematic efficiency of near-circular trajectories, this algorithm achieves higher sampling rates than shortest path approaches, while retaining a relatively efficient coverage fraction in comparison to raster or resonance based frame-scanning approaches.
Solving SameGame and its Chessboard Variant

We introduce a new solving method for SameGame puzzles based on Monte-Carlo simulation, that improves the previous best known method. We also cover the ches sboard variant, a subclass of the SameGame puzzle for which we can exactly define which puzzles are solva ble nd which ones are not. Next to this we present a quantitative approach to classify the difficult y of a given puzzle, as well as an indication of whether or not a given puzzle is solvable.
Empirical Evaluation of Cost Overrun Prediction with Imbalance Data

To prevent cost overrun of software projects, it is necessary for project managers to identify projects which have high risk of cost overrun in the early phase. So far, discriminant methods such as linear discriminant analysis and logistic regression have been used to predict cost overrun projects. However, accuracy of discriminant methods often becomes low when a dataset used for predict is imbalanced, i.e. there exists a large difference between the number of cost overrun projects and non cost overrun projects. In this paper, we compared accuracy of linear discriminant analysis, logistic regression, classification tree, Mahalanobis-Taguchi method, and collaborative filtering, by changing the percentage of cost overrun projects in the dataset. The result showed that collaborative filtering was highest accuracy among five methods. When the number of cost overrun projects and non cost overrun was balanced in the dataset, linear discriminant analysis was second highest accuracy, and when it was not balanced, Mahalanobis-Taguchi method was second highest among five methods.
Relationship of Anagram Solving to Measures of Divergent-Production and Letter-Rearrangement Ability

Summary An anagram test and several tests of divergent-production and letter-rearrangement were administered to undergraduate psychology students. Significant positive relationships were obtained for all comparisons, with high-scoring anagram solvers producing significantly more responses on each of these measures than low-scoring solvers. The findings provided evidence for the presence of divergent-production ability in anagram solving and permitted the conclusion that measures of flexibility and letter-rearrangement are clearly related to the solution of conventional anagram problems.
Multi-Objective Trajectory Planning with Dual-Encoder

Time-jerk optimal trajectory planning is crucial in advancing robotic arms' performance in dynamic tasks. Traditional methods rely on solving complex nonlinear programming problems, bringing significant delays in generating optimized trajectories. In this paper, we propose a two-stage approach to accelerate time-jerk optimal trajectory planning. Firstly, we introduce a dual-encoder based transformer model to establish a good preliminary trajectory. This trajectory is subsequently refined through sequential quadratic programming to improve its optimality and robustness. Our approach outperforms the state-of-the-art by up to 79.72\% in reducing trajectory planning time. Compared with existing methods, our method shrinks the optimality gap with the objective function value decreasing by up to 29.9\%.
Improving the Spatial Correlation Characteristics of Antenna Arrays using Linear Operators and Wide-band Modelling

The analysis of wireless communication channels at the mmWave, sub-THz and THz bands gives rise to difficulties in the construction of antenna arrays due to the small maximum inter-element spacing constraints at these frequencies. Arrays with uniform spacing greater than half the wavelength for a certain carrier frequency exhibit aliasing side-lobes in the angular domain, prohibiting non-ambiguous estimates of a propagating wave-front's angle of arrival. In this paper, we present how wide-band modelling of the array response is useful in mitigating this spatial aliasing effect. This approach aims to reduce the grating lobes by exploiting the angle- and frequency-dependent phase-shifts observed in the response of the array to a planar wave-front travelling across it. Furthermore, we propose a method by which the spatial correlation characteristics of an array operating at 33 GHz carrier frequency with an instantaneous bandwidth of 1 GHz can be improved such that the angular-domain side-lobes are reduced by 5-10 dB. This method, applicable to arbitrary antenna array manifolds, makes use of a linear operator that is applied to the base-band samples of the channel transfer function measured in space and frequency domains. By means of synthetically simulated arrays, we show that when operating with a bandwidth of 1 GHz, the use of a derived linear operator applied to the array output results in the spatial correlation characteristics approaching those of the array operating at a bandwidth of 12 GHz. Hence, non-ambiguous angle estimates can be obtained in the field without the use of expensive high-bandwidth RF front-end components.
Cardiovascular risk in Japanese-Brazilian subjects.

OBJECTIVE To evaluate the prevalence of risk factors for cardiovascular disease in Japanese-Brazilian subjects. SUBJECTS AND METHODS One hundred thirty-one residents of the Mombuca community were studied. Statistical analysis was based on the X² test, Fisher's Exact test, Student's t test, and ANOVA, at a 5% significance level. RESULTS The average age was 56.7 years-old; 76.3% had dyslipidemia, 24.4% pre-diabetes (PDM), 10.7% type 2 diabetes mellitus (T2DM), 46.6% hypertension, 52.7% abdominal obesity, and 35.8% metabolic syndrome (MS). There were significant correlations between HOMA-IR and MS diagnosis and obesity, while HOMA-β levels were decreased in T2DM and PDM. The ankle-brachial index was positive for peripheral artery disease in 22.3% of the individuals. Electrocardiograms did not show increased evidence of myocardial ischemia. CONCLUSION Subjects of this community are exposed to major cardiovascular risk factors, namely high prevalence of MS diagnoses and increased HOMA-IR.
Avoidance of Affect Mediates the Effect of Invalidating Childhood Environments on Borderline Personality Symptomatology in a Non-Clinical Sample.

Abstract The aim of this study was to test the Linehan (1993) proposal regarding associations between invalidating childhood environments, distress tolerance (e.g., avoidance of affect), and borderline personality disorder (BPD) symptoms. The sample consisted of 141 non-clinical participants (51 men, 89 women, one gender unknown), ranging in age from 18 to 71 years (M = 35.17 years, SD = 13.89). The questionnaire package explored childhood environment, methods of coping with distress, and BPD features. Results indicated that reports of maternal invalidation were significantly correlated with avoidance of affect and BPD (p < .05). Mediation analysis indicated that avoidance of affect mediated the relationship between maternal invalidation and BPD. Consistent with the Linehan (1993) model, pervasive parental invalidation and avoidance of affect are considered potentially important constructs in the development and maintenance of BPD. This research contributes to the general understanding of BPD and may assi.
Quality of attachment in the preschool years

Abstract This is a theoretical paper about differences in quality of attachment in preschool-aged children with emphasis on the development of the goal-corrected partnership. Inferences are made about the processes underlying preschoolers' attachment behavior. Specifically, the notion of quality of attachment is expanded to explicitly include strategy, regulation of affect, negotiation, secure base behavior, and response to maternal behavior. The classificatory system is expanded by adding two additional defended patterns, that is, compulsive caregiving and compulsive compliance, to the infant avoidant pattern. Furthermore, at the preschool age, the infant ambivalent pattern is identified as having a coercive strategy. In addition, the disorganized infant category is reconceptualized in terms of complex organization, reorganization, and disorganization. Finally, the process of generating new theories and hypotheses through a “participant observer” methodology is considered from the perspective of developmental psychopathology.
An Online Data Compression Algorithm for Trajectories (An OLDCAT)

 Abstract—In the regime of "Big Data", data compression techniques take crucial part in preparation phase of data analysis. It is challenging because statistical properties and other characteristics need to be preserved while the size of data need to be reduced. In particular, to compress trajectory data, movement status (such as position, direction, and speed etc.) need to be retained. Moreover, for the increasing demand of real-time processing capability, "online" algorithms are becoming more desirable in data analysis. In this paper, we
Using regression analysis for GA-based ATPG parameter optimization

Genetic algorithms have proven to be a viable solution to the NP-complete problem of test vector generation. However the parameters used to control GA-based ATPG can greatly affect test set size, fault coverage and CPU execution time. Knowing how a given set of parameters will affect each of these factors a priori allows for more efficient testing procedures. Over 1 million ATPG experiments were conducted on the ISCAS85 benchmark set exploring a wide range of parameter options. Although sequential circuit testing looms as the larger problem, investigating combinational circuits should provide direction as to where efforts should be focused. From our experiments, we derive regression-based equations utilizing circuit characteristics and various controllable parameters. Using these equations, the ATPG tool determines parameter values that maximize fault coverage while meeting constraints on CPU run times and test set size. For many circuits tested, fault coverage improved with a tolerable increase in CPU time.
Flavonoids and Colorectal Cancer in Italy

Because of their several biological activities, flavonoids may have an important role in explaining the protective effects of vegetables, fruit, and, possibly, tea against cancer. The potential relation between flavonoids and colorectal cancer risk was investigated using data from a multicentric Italian case-control study, including 1,953 cases of colorectal cancers (1,225 colon cancers and 728 rectal cancers) and 4,154 hospital controls admitted for acute nonneoplastic diseases. We have applied recently published data on the composition of foods and beverages, in terms of six principal classes of flavonoids, on dietary information collected through a validated food-frequency questionnaire. Odds ratios (OR) were estimated by multiple logistic regression models, including terms for sex, age, study center, family history of colorectal cancer, education, alcohol consumption, body mass index, physical activity, and energy intake. A reduced risk of colorectal cancer was found for increasing intake of isoflavones (OR, 0.76, for the highest versus the lowest quintile, Ptrend = 0.001), anthocyanidins (OR, 0.67, Ptrend < 0.001), flavones (OR, 0.78, Ptrend = 0.004), and flavonols (OR, 0.64, Ptrend < 0.001). No significant association was found for flavan-3-ols (OR, 0.98), flavanones (OR, 0.96), and total flavonoids (OR, 0.97). The estimates did not substantially differ for colon and rectal cancers, as well as in strata of sex, age, and body mass index. The findings of this large study provide support for an inverse association of selected classes of flavonoids with colorectal cancer risk. (Cancer Epidemiol Biomarker Prev 2006;15(8):1555–8)
Association for Information Systems Year I ’ m Losing Patience with your Site : The Impact of Information Scent and Time Constraints on Effort , Performance , and Attitudes

As competition increases in the online world, website owners will investigate ways in which they can attract more users. Additionally, many consumers suffer ever-increasing time limitations when browsing for a particular item on a website. Users can become frustrated and stressed when they are unable to find those items due to poor information scent, or semantic cues that are meant to lead to their goal. This paper presents and tests a theoretical model to predict how information scent can reduce the amount of stress that consumers experience when seeking information under time constraints. The study also demonstrates the relationships between information scent, time constraints, stress, performance and attitudes toward the website. Results indicate that while high information scent is an important design goal, scent can only be assessed by taking the user’s task into account.
Real-time multitarget tracking by a cooperative distributed vision system

Target detection and tracking is one of the most important and fundamental technologies to develop real-world computer vision systems such as security and traffic monitoring systems. This paper first categorizes target tracking systems based on characteristics of scenes, tasks, and system architectures. Then we present a real-time cooperative multitarget tracking system. The system consists of a group of active vision agents (AVAs), where an AVA is a logical model of a network-connected computer with an active camera. All AVAs cooperatively track their target objects by dynamically exchanging object information with each other With this cooperative tracking capability, the system as a whole can track multiple moving objects persistently even under complicated dynamic environments in the real world. In this paper we address the technologies employed in the system and demonstrate their effectiveness.
Students Make Sure the Cherokees are Not Removed … Again: A Study of Service-Learning and Artful Learning in Teaching History

Bringing history alive in one Southern, suburban middle school, this application of community-action service-learning and Artful Learning is chronicled from inception to conclusion. This qualitative participatory action research study explored the effects of this program on 8th-grade gifted students. The purpose of the study was to examine one specific, successful program involving gifted students in a Learn and Serve America grant project site in reference to the service-learning and Artful Learning Models. The results showed improved achievement and suggested enhanced metacognition, self-efficacy, and altruism. The students were actively involved in their own learning, eventually making a difference in their community.