Miracle-dz/UniFAR-FTUs huggingface dataset:
Meta Modeling for Combinatorial Catalyst Optimization

†† Summary Our aim is to find the best catalyst, the best combination of compounds, in order to optimize a chemical reaction. The chemists use mainly a heuristic algorithm, especially an evolutionary algorithm, to achieve the best combination. In this paper, we outline a variant of evolutionary optimization algorithm, says meta modeling. Our idea is to combine a statistical learning algorithm with the optimization process. The goal is a better use of the past experience, the labelled individuals, in the guidance of the search exploration of the optimal solution. The approach is especially useful in the combinatorial catalysis optimization because the fitness function is unknown and the labelled individual is obtained by real chemical reaction. This is highly costly and takes time. We show on a well-known chemists' benchmark that our process slightly the average performance of the standard evolutionary algorithms. But numerous problems remain opened. We try to inventory them in order to define our future work to improve the approach.
An improved interpretation of Mason's model for piezoelectric plate transducers

A new interpretation of Mason¿s model (1948) for a piezoelectric plate transducer is presented. The network model emphasizes a series connection for the two acoustic loads while utilizing lumped impedance elements expressed 88 functions of the delay operator Z = exp ST. An exact analysis of the plate dynamics permits a simplifii resistive model for conditions of light asymmetry in acoustic loading. A simplified resistive structure provides transmission (reception) loss near the halfwave resonance. Air backed front loading b modeled. Finally, RLC lumped component models are provided fo1 evaluation of transducers as lumped-element filters.
Screening Driving Transcription Factors in the Processing of Gastric Cancer

Background. Construction of the transcriptional regulatory network can provide additional clues on the regulatory mechanisms and therapeutic applications in gastric cancer. Methods. Gene expression profiles of gastric cancer were downloaded from GEO database for integrated analysis. All of DEGs were analyzed by GO enrichment and KEGG pathway enrichment. Transcription factors were further identified and then a global transcriptional regulatory network was constructed. Results. By integrated analysis of the six eligible datasets (340 cases and 43 controls), a bunch of 2327 DEGs were identified, including 2100 upregulated and 227 downregulated DEGs. Functional enrichment analysis of DEGs showed that digestion was a significantly enriched GO term for biological process. Moreover, there were two important enriched KEGG pathways: cell cycle and homologous recombination. Furthermore, a total of 70 differentially expressed TFs were identified and the transcriptional regulatory network was constructed, which consisted of 566 TF-target interactions. The top ten TFs regulating most downstream target genes were BRCA1, ARID3A, EHF, SOX10, ZNF263, FOXL1, FEV, GATA3, FOXC1, and FOXD1. Most of them were involved in the carcinogenesis of gastric cancer. Conclusion. The transcriptional regulatory network can help researchers to further clarify the underlying regulatory mechanisms of gastric cancer tumorigenesis.
Preliminary study of online gait recognizer for lower limb exoskeletons

We propose a novel two-tier gait recognizer using a minimal number of mechanical sensors built into a lower limb exoskeleton. The aim of this recognizer is to offer one-step selection of one of the actions ascending, descending, and level walking during five gaits (stair ascent/descent, slope ascent/descent, level walking). The proposed recognizer is executed at the moment of foot contact as estimated by an inertial measurement unit (IMU) on the pelvis without using direct foot sensors. The proposed recognizer selects the gait by using the relations between the angles formed by the hip and knee joints during the last step. As this study constitutes preliminary work for lower limb exoskeletons, we used a hip exoskeleton integrated with two wireless IMUs on the shank to set up the lower limb exoskeleton sensor configuration. Experiments were used to evaluate IMU-based foot contact estimation with respect to a foot sensor based on a force-sensitive resistor (FSR) for stairs, slopes, and level ground. In addition, we evaluated the performance of the proposed two-tier gait recognizer by using two healthy male subjects in various gait environments.
Speaker indexing in large audio databases using anchor models

Introduces the technique of anchor modeling in the applications of speaker detection and speaker indexing. The anchor modeling algorithm is refined by pruning the number of models needed. The system is applied to the speaker detection problem where its performance is shown to fall short of the state-of-the-art Gaussian mixture model with universal background model (GMM-UBM) system. However, it is further shown that its computational efficiency lends itself to speaker indexing for searching large audio databases for desired speakers. Here, excessive computation may prohibit the use of the GMM-UBM recognition system. Finally, the paper presents a method for cascading anchor model and GMM-UBM detectors for speaker indexing. This approach benefits from the efficiency of anchor modeling and high accuracy of GMM-UBM recognition.
OARPLAN: Generating project plans by reasoning about objects, actions and resources

This paper describes OARPLAN, a prototype planning system that generates construction project plans from a description of the objects that comprise the completed facility. OARPLAN is based upon the notion that activities in a project plan can be viewed as intersections of their constituents: objects, actions and resources. Planning knowledge in OARPLAN is represented as constraints based on activity constituents and their interrelationships; the planner functions as a constraint satisfaction engine that attempts to satisfy these constraints. The goal of the OARPLAN project is to develop a planning shell for construction projects that (i) provides a natural and powerful constraint language for expressing knowledge about construction planning, and (ii) generates a facility construction plan by satisfying constraints expressed in this language. To generate its construction plan, OARPLAN must be supplied with extensive knowledge about construction objects, actions and resources, and about spatial, topological, temporal and other relations that may exist between them. We suggest that much of the knowledge required to plan the construction of a given facility can be drawn directly from a three-dimensional CAD model of the facility, and from a variety of databases currently used in design and project management software. In the prototype OARPLAN system, facility data must be input directly as frames. However, we are collaborating with database researchers to develop intelligent interfaces to such sources of planning data, so that OARPLAN will eventually be able to send high level queries to an intelligent database access system without regard for the particular CAD system in which the project was designed. We begin by explaining why classical AI planners and domain specific expert system approaches are both inadequate for the task of generating construction project plans. We describe the activity representation developed in OARPLAN and demonstrate its use in producing a plan of about 50 activities for a steel-frame building, based on spatial and topological constraints that express structural support, weather protection and safety concerns in construction planning. We conclude with a discussion of the research issues raised by our experiments with OARPLAN to date.
An Interior-Point Lagrangian Decomposition Method for Separable Convex Optimization

In this paper, we propose a distributed algorithm for solving large-scale separable convex problems using Lagrangian dual decomposition and the interior-point framework. By adding self-concordant barrier terms to the ordinary Lagrangian, we prove under mild assumptions that the corresponding family of augmented dual functions is self-concordant. This makes it possible to efficiently use the Newton method for tracing the central path. We show that the new algorithm is globally convergent and highly parallelizable and thus it is suitable for solving large-scale separable convex problems.
Simultaneous imaging of haemoglobin oxygenation and blood flow with RGB reflectometry and LASCA during stroke in rats

We demonstrate the simultaneous mapping of haemoglobin oxygenation and blood flow changes of human skin and the exposed cortex in rats by broad-band reflectometry and laser speckle contrast analysis (LASCA). A hard- and software set-up is realized with a high temporal resolution achieved by techniques of multi- and manycore computing. Spatial and temporal resolved changes of haemoglobin oxygenation and blood flow in rats are observed in response to middle cerebral artery occlusion and cortical spreading depression.
Exogenous α-synuclein fibrils seed the formation of Lewy body-like intracellular inclusions in cultured cells

Cytoplasmic inclusions containing α-synuclein (α-Syn) fibrils, referred to as Lewy bodies (LBs), are the signature neuropathological hallmarks of Parkinson's disease (PD). Although α-Syn fibrils can be generated from recombinant α-Syn protein in vitro, the production of fibrillar α-Syn inclusions similar to authentic LBs in cultured cells has not been achieved. We show here that intracellular α-Syn aggregation can be triggered by the introduction of exogenously produced recombinant α-Syn fibrils into cultured cells engineered to overexpress α-Syn. Unlike unassembled α-Syn, these α-Syn fibrils “seeded” recruitment of endogenous soluble α-Syn protein and their conversion into insoluble, hyperphosphorylated, and ubiquitinated pathological species. Thus, this cell model recapitulates key features of LBs in human PD brains. Also, these findings support the concept that intracellular α-Syn aggregation is normally limited by the number of active nucleation sites present in the cytoplasm and that small quantities of α-Syn fibrils can alter this balance by acting as seeds for aggregation.
Validation of microRNA pathway polymorphisms in esophageal adenocarcinoma survival

Polymorphisms in miRNA and miRNA pathway genes have been previously associated with cancer risk and outcome, but have not been studied in esophageal adenocarcinoma outcomes. Here, we evaluate candidate miRNA pathway polymorphisms in esophageal adenocarcinoma prognosis and attempt to validate them in an independent cohort of esophageal adenocarcinoma patients. Among 231 esophageal adenocarcinoma patients of all stages/treatment plans, 38 candidate genetic polymorphisms (17 biogenesis, 9 miRNA targets, 5 pri‐miRNA, 7 pre‐miRNA) were genotyped and analyzed. Cox proportional hazard models adjusted for sociodemographic and clinicopathological covariates helped assess the association of genetic polymorphisms with overall survival (OS) and progression‐free survival (PFS). Significantly associated polymorphisms were then evaluated in an independent cohort of 137 esophageal adenocarcinoma patients. Among the 231 discovery cohort patients, 86% were male, median diagnosis age was 64 years, 34% were metastatic at diagnosis, and median OS and PFS were 20 and 12 months, respectively. GEMIN3 rs197412 (aHR = 1.37, 95%CI: [1.04–1.80]; P = 0.02), hsa‐mir‐124‐1 rs531564 (aHR = 0.60, 95% CI: [0.53–0.90]; P = 0.05), and KIAA0423 rs1053667 (aHR = 0.51, 95% CI: [0.28–0.96]; P = 0.04) were found associated with OS. Furthermore, GEMIN3 rs197412 (aHR = 1.33, 95% CI: [1.03–1.74]; P = 0.03) and KRT81 rs3660 (aHR = 1.29, 95% CI: [1.01–1.64]; P = 0.04) were found associated with PFS. Although none of these polymorphisms were significant in the second cohort, hsa‐mir‐124‐1 rs531564 and KIAA0423 rs1053667 had trends in the same direction; when both cohorts were combined together, GEMIN3 rs197412, hsa‐mir‐124‐1 rs531564, and KIAA0423 rs1053667 remained significantly associated with OS. We demonstrate the association of multiple miRNA pathway polymorphisms with esophageal adenocarcinoma prognosis in a discovery cohort of patients, which did not validate in a separate cohort but had consistent associations in the pooled cohort. Larger studies are required to confirm/validate the prognostic value of these polymorphisms in esophageal adenocarcinoma.
Low-Power Design of Delay-Constrained Circuits Using Dual-V T Process Technology

This paper addresses low-power circuit design for delay-constrained portions of cutting-edge ICs, in which scaled threshold voltages have made leakage power consumption a major concern. Assuming parameters for a dual-VT 0.10-μm process generation, we analyze two different circuits, using low-VT and high-VT devices, respectively, obeying an identical delay constraint. The power consumption comparison shows that counteracting leakage currents by replacing low-VT with high-VT devices may lead to a rapidly increasing total power consumption. This is caused by an increasing switching power, due to the dramatic sizing required in the high-VT circuit to make it satisfy the delay constraint.
Dynamic programming search for continuous speech recognition

The authors gives a unifying view of the dynamic programming approach to the search problem. They review the search problem from the statistical point-of-view and show how the search space results from the acoustic and language models required by the statistical approach. Starting from the baseline one-pass algorithm using a linear organization of the pronunciation lexicon, they have extended the baseline algorithm toward various dimensions. To handle a large vocabulary, they have shown how the search space can be structured in combination with a lexical prefix tree organization of the pronunciation lexicon. In addition, they have shown how this structure of the search space can be combined with a time-synchronous beam search concept and how the search space can be constructed dynamically during the recognition process. In particular, to increase the efficiency of the beam search concept, they have integrated the language model look-ahead into the pruning operation. To produce sentence alternatives rather than only the single best sentence, they have extended the search strategy to generate a word graph. Finally, they have reported experimental results on a 64 k-word task that demonstrate the efficiency of the various search concepts presented.
Yeast protein function motif extraction based on sequence alignment

Protein function prediction is one of the most important problems in the field of proteomics since it leads to determining cell functions. Since proteome is divided into clusters, each cluster (group of proteins) should have common characteristics. One of these characteristics is to have the same functions. In this study we try to extract motifs for each sub-function category of yeast proteins. The technique is based on applying multiple sequence alignment (MSA) to all yeast protein function categories. The protein sequences are collected from different data sources as DIP, PIR, and SWISS PROT and CLC program is used to apply the sequence alignment. Threshold is determined for every protein function category to indicate the most common frequent amino acids to be a feature for this category. After implementing the algorithm, sequence is verified with some proteins have the correct functions and the gained results are good. The technique is considered as verification method for protein function prediction
Middleware for Incremental Processing in Conversational Agents

We describe work done at three sites on designing conversational agents capable of incremental processing. We focus on the 'middleware' layer in these systems, which takes care of passing around and maintaining incremental information between the modules of such agents. All implementations are based on the abstract model of incremental dialogue processing proposed by Schlangen and Skantze (2009), and the paper shows what different instantiations of the model can look like given specific requirements and application areas.
Experimenting with the use of persona in a focus group discussion with older adults in Malaysia

Eliciting user-requirements from older adults -- especially amongst non-users -- can be challenging. This is due to the fact that older adults are varied in term of their functional abilities and experience with technology. The common User-centered design (UCD) techniques such as focus group and interviews were found to be less effective with older adults. Inspired by the benefits of persona in enhancing designer's attention through narrative and storytelling, the study reported in this paper tested persona as a communication tool in a focus group discussion with older adults in Malaysia. The study was carried out to gather Malaysian older adults' needs and requirements for the development of a prototype email application. Findings and feedbacks from the study shows that persona can be a potential technique to be applied in working with older adults. The use of persona in a focus group discussion does not only benefit the researchers and designers but also the participants -- particularly in building interest among non-users to embrace computers.
Repeated injections of D-Amphetamine evoke rapid and dynamic changes in phase synchrony between the prefrontal cortex and hippocampus

Repeated drug use evokes a number of persistent alterations in oscillatory power and synchrony. How synchronous activity in cortico-hippocampal circuits is progressively modified with repeated drug exposure, however, remains to be characterized. Drugs of abuse induce both short-term and long-term adaptations in cortical and hippocampal circuits and these changes are likely important for the expression of the altered behavioral and neurobiological phenotype associated with addiction. The present study explores how the initial (up to 1 h) pharmacological response to D-Amphetamine (AMPH) is altered with repeated injections in the rat. The methods employed herein allow for the progressive changes in synchronized dynamics with repeated intermittent AMPH exposure to be characterized over short time scales (minutes). Specifically, we examined the temporal variations of phase-locking strength in delta and theta bands within the prefrontal cortex (PFC) and between PFC and hippocampus (HC) shortly after drug injection. After the first injection of AMPH synchrony increased within the PFC in the delta band, which was followed, by an increase in theta synchrony between the PFC and HC several minutes later. This relationship switched after repeated AMPH injections, where increases in theta synchrony between the PFC and HC preceded increases in delta synchrony in the PFC. The time-course of increases in synchronous activity were negatively correlated between the PFC delta and the PFC-HC theta. Collectively these data highlight the potential role of PFC-HC circuits in the development of addiction and outline dynamic changes in the time-course that cortico-hippocampal circuits become synchronized with repeated AMPH exposure.
Towards policy-based management of sensor networks

Contemporary distributed software systems for realistic business applications have become extremely heterogeneous, dynamic and large scale. They offer services to many different types of users and include various hardware such as backend servers, regular PCs and various mobile and embedded devices, as well as diverse network infrastructures, such as sensor networks. However, managing these systems is typically a complicated task due to several factors. This paper proposes a policy-based approach that offers a higher level of abstraction to manage these distributed applications in an easier way. We first give an overview of existing research on policies in traditional middleware and describe some of the shortcomings when applying them for managing sensor networks. Secondly, we propose an architecture for a policy-driven middleware that addresses these limitations and provides a solution for them.
#Sleep_as_Android: Feasibility of Using Sleep Logs on Twitter for Sleep Studies

Social media enjoys a growing popularity as a platform to seek and share personal health information. For sleep studies using data from social media, most researchers focused on inferring sleep-related artifacts from self-reported anecdotal pointers to sleep patterns or issues such as insomnia. The data shared by "quantified-selfers" on social media presents an opportunity to study more quantitative and objective measures of sleep. We propose and validate the approach of collecting and analyzing sleep logs that are generated and shared through a sleep-tracking mobile application. We highlight the value of this data by combining it with users' social media data. The results provide a validation of using social media for sleep studies as the collected sleep data is aligned with sleep data from other sources. The results of combining social media data with sleep data provide preliminary evidence that higher social media activity is associated with lower sleep duration and quality.
Restoring Blood-Brain Barrier P-Glycoprotein Reduces Brain Amyloid-β in a Mouse Model of Alzheimer's Disease

Reduced clearance of amyloid-β (Aβ) from brain partly underlies increased Aβ brain accumulation in Alzheimer's disease (AD). The mechanistic basis for this pathology is unknown, but recent evidence suggests a neurovascular component in AD etiology. We show here that the ATP-driven pump, P-glycoprotein, specifically mediates efflux transport of Aβ from mouse brain capillaries into the vascular space, thus identifying a critical component of the Aβ brain efflux mechanism. We demonstrate in a transgenic mouse model of AD [human amyloid precursor protein (hAPP)-overexpressing mice; Tg2576 strain] that brain capillary P-glycoprotein expression and transport activity are substantially reduced compared with wild-type control mice, suggesting a mechanism by which Aβ accumulates in the brain in AD. It is noteworthy that dosing 12-week-old, asymptomatic hAPP mice over 7 days with pregnenolone-16α-carbonitrile to activate the nuclear receptor pregnane X receptor restores P-glycoprotein expression and transport activity in brain capillaries and significantly reduces brain Aβ levels compared with untreated control mice. Thus, targeting intracellular signals that up-regulate blood-brain barrier P-glycoprotein in the early stages of AD has the potential to increase Aβ clearance from the brain and reduce Aβ brain accumulation. This mechanism suggests a new therapeutic strategy in AD.
Management of pain associated with metastatic epidural spinal cord compression: use of imaging studies in planning epidural therapy

Direct or metastatic spread of malignancy to involve the epidural space can lead to spinal cord compression and paraplegia. Compression of the spinal cord by metastatic tumor is a common neurologic complication of advanced cancer.1 Epidural metastases are most often associated with lung, breast, prostate, kidney, and hematologic malignancies in decreasing order of frequencies.2 Patients with epidural metastases causing spinal cord compression present with back pain with or without radicular pain followed weeks to months later by onset of neurologic deficit.2 Neuropathic pain associated with partial compression of the spinal cord and exiting nerve roots can be extraordinarily difficult to manage. We describe a man with metastatic lung cancer involving the epidural space and intractable neuropathic pain. An implanted epidural catheter was used to successfully manage his pain. We focus on the usefulness of imaging studies to effectively manage epidural analgesia in the presence of metastatic cancer involving the epidural space.