Miracle-dz/UniFAR-FTUs huggingface dataset:
DEFORMATION MEASUREMENT OF CON-DUCTING POLYTHIOPHENE THIN FILMS BY AN ELECTRONIC SPECKLE PATTERN INTERFEROMETRIC METHOD

The deformation measurement of electrosynthesized polythiophene(Pth)thin films is difficultbecause of the small thickness and high flexibility of the specimen.An electronic speckle pattern interferom-etry(ESPI)method is used to measure the deformation of Pth films of thicknesses in the range of 4-65 μmTheir stress-strain curves are obtained.It is found that the mechanical properties of Pth films are sensitiveto the specimen thickness.The tensile strength increases with decreasing thickness of thin film from 10 μm. The influence of the electrochemical synthesis conditions on the mechanical properties of Pth films is also dis-cussed.
Improving succinylation prediction accuracy by incorporating the secondary structure via helix, strand and coil, and evolutionary information from profile bigrams

Post-translational modification refers to the biological mechanism involved in the enzymatic modification of proteins after being translated in the ribosome. This mechanism comprises a wide range of structural modifications, which bring dramatic variations to the biological function of proteins. One of the recently discovered modifications is succinylation. Although succinylation can be detected through mass spectrometry, its current experimental detection turns out to be a timely process unable to meet the exponential growth of sequenced proteins. Therefore, the implementation of fast and accurate computational methods has emerged as a feasible solution. This paper proposes a novel classification approach, which effectively incorporates the secondary structure and evolutionary information of proteins through profile bigrams for succinylation prediction. The proposed predictor, abbreviated as SSEvol-Suc, made use of the above features for training an AdaBoost classifier and consequently predicting succinylated lysine residues. When SSEvol-Suc was compared with four benchmark predictors, it outperformed them in metrics such as sensitivity (0.909), accuracy (0.875) and Matthews correlation coefficient (0.75).
Lock and chop: A novel method for the generation of a PICK1 PDZ domain and piperidine‐based inhibitor co‐crystal structure

The membrane protein interacting with kinase C1 (PICK1) plays a trafficking role in the internalization of neuron receptors such as the amino‐3‐hydroxyl‐5‐methyl‐4‐isoxazole‐propionate (AMPA) receptor. Reduction of surface AMPA type receptors on neurons reduces synaptic communication leading to cognitive impairment in progressive neurodegenerative diseases such as Alzheimer disease. The internalization of AMPA receptors is mediated by the PDZ domain of PICK1 which binds to the GluA2 subunit of AMPA receptors and targets the receptor for internalization through endocytosis, reducing synaptic communication. We planned to block the PICK1‐GluA2 protein–protein interaction with a small molecule inhibitor to stabilize surface AMPA receptors as a therapeutic possibility for neurodegenerative diseases. Using a fluorescence polarization assay, we identified compound BIO124 as a modest inhibitor of the PICK1‐GluA2 interaction. We further tried to improve the binding affinity of BIO124 using structure‐aided drug design but were unsuccessful in producing a co‐crystal structure using previously reported crystallography methods for PICK1. Here, we present a novel method through which we generated a co‐crystal structure of the PDZ domain of PICK1 bound to BIO124.
Statistical tests and identifiability conditions for pooling and analyzing multisite datasets

Significance How can one efficiently combine experimental and observational predictive data from different laboratories into a single predictive model when the laboratories have differently calibrated measuring instruments and the study populations have different demographic distributions? When both differences exist in the data, important quantities may not be identifiable, but we provide sufficient conditions for when they are and practical plans to account for the differences, including subsampling. The methods are applied to two Alzheimer’s disease studies, where measured cerebral spinal fluid and demographic data show differences, and we seek to identify associations with a response variable. We provide tools to add to the armamentarium of the scientific experimenter and data analyst for efficient combination of information from diverse sources. When sample sizes are small, the ability to identify weak (but scientifically interesting) associations between a set of predictors and a response may be enhanced by pooling existing datasets. However, variations in acquisition methods and the distribution of participants or observations between datasets, especially due to the distributional shifts in some predictors, may obfuscate real effects when datasets are combined. We present a rigorous statistical treatment of this problem and identify conditions where we can correct the distributional shift. We also provide an algorithm for the situation where the correction is identifiable. We analyze various properties of the framework for testing model fit, constructing confidence intervals, and evaluating consistency characteristics. Our technical development is motivated by Alzheimer’s disease (AD) studies, and we present empirical results showing that our framework enables harmonizing of protein biomarkers, even when the assays across sites differ. Our contribution may, in part, mitigate a bottleneck that researchers face in clinical research when pooling smaller sized datasets and may offer benefits when the subjects of interest are difficult to recruit or when resources prohibit large single-site studies.
Title Dense cranial electroacupuncture stimulation for major depressive disorder-A single-blind , randomized , controlled study

Background: Previous studies suggest that electroacupuncture possesses therapeutic benefits for depressive disorders. The purpose of this study was to determine whether dense cranial electroacupuncture stimulation (DCEAS) could enhance the antidepressant efficacy in the early phase of selective serotonin reuptake inhibitor (SSRI) treatment of major depressive disorder (MDD). Methods: In this single-blind, randomized, controlled study, patients with MDD were randomly assigned to 9-session DCEAS or noninvasive electroacupuncture (n-EA) control procedure in combination with fluoxetine (FLX) for 3 weeks. Clinical outcomes were measured using the 17-item Hamilton Depression Rating Scale (HAMD-17), Clinical Global Impressionseverity (CGI-S), and Self-rating Depression Scale (SDS) as well as the response and remission rates. Results: Seventy-three patients were randomly assigned to n-EA (n = 35) and DCEAS (n = 38), of whom 34 in n-EA and 36 in DCEAS group were analyzed. DCEAS-treated patients displayed a significantly greater reduction from baseline in HAMD-17 scores at Day 3 through Day 21 and in SDS scores at Day 3 and Day 21 compared to patients receiving n-EA. DCEAS intervention also produced a higher rate of clinically significant response compared to n-EA procedure (19.4% (7/36) vs. 8.8% (3/34)). The incidence of adverse events was similar in the two groups. Conclusions: DCEAS is a safe and effective intervention that augments the antidepressant efficacy. It can be considered as an additional therapy in the early phase of SSRI treatment of depressed patients. Trial Registration: Controlled-Trials.com ISRCTN88008690 Citation: Zhang Z-J, Ng R, Man SC, Li TYJ, Wong W, et al. (2012) Dense Cranial Electroacupuncture Stimulation for Major Depressive Disorder—A Single-Blind, Randomized, Controlled Study. PLoS ONE 7(1): e29651. doi:10.1371/journal.pone. 0029651 Editor: Kenji Hashimoto, Chiba University Center for Forensic Mental Health, Japan Received September 7, 2011; Accepted November 30, 2011; Published January 6, 2012 Copyright: 2012 Zhang et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This study was supported by Health and Health Services Research Fund (HHSRF) from Food and Health Bureau of Hong Kong (ref. No.: 06070831). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. * E-mail: zhangzj@hku.hk
Methods and demographic findings of the baseline survey of the NEDICES cohort : a door-to-door survey of neurological disorders in three communities from Central Spain

Department of Research, Ministry of Labour and Social Affairs, Madrid, Spain Department of Neurology, University Hospital ‘12 de Octubre’, Madrid, Spain Department of Neurology, Móstoles General Hospital, Madrid, Spain Area for Applied Epidemiology, NationalCentre for Epidemiology, InstituteofHealthCarlos III, Madrid, Spain Section of Clinical Epidemiology, University Hospital ‘Princesa’, Madrid, Spain Arévalo Health Centre, Arévalo, Segovia, Spain The NEDICES (Neurological Disorders in Central Spain) Study Group. Main investigators of the three locations: Margaritas, FBP; Lista, RGS; Arévalo, SVQ. Main investigator of the WHO-AAD Project: Alberto Portera-Sánchez. Neurologists: Jaime Dı́az, Cristina Fernández, JA Molina S, Javier Olazarán, Javier Rodrı́guez, JBL and FBP. Supervisors: Fernando Pérez del Molino, JRN, Margarita Alonso, Candelas Gómez and Carmen Saiz. Informatics: Guillermo Fernández J. Statistical analysis: RT and Paz Rodrı́guez. Epidemiologists: JMM and RGS.
Social Media Analytics: Literature Review and Directions for Future Research

Businesses are currently using social media analytics SMA to develop insights for improving performance and productivity across different functions. The SMA knowledge is growing diversely, and there is a need to understand the trends and approaches holistically. The present paper offers a comprehensive review of the SMA empirical literature and directions for future research. The review is based on 54 papers selected out of 843 search results. The review focuses on different domains: industrial domains, data-mining objectives, use cases, and applications. Out of the studies, public administration and consumer discretionary sectors are the dominant ones with Twitter data being used in most of the analysis. Out of the possible techniques, classification techniques and regression models are more popular than others. Stakeholder engagement is the most focused theme in the research studies. The review also offers insights into which analytical approaches are being used in which industrial domains for specific decision making. It further suggests that novel methods, such as cross-media data classification, tags detection, label priority ranking, tweeting activity signatures, and geospatial data processing have been used less and could be further explored in future research. The review also offers implications for the decision sciences domain.
Several examinations on the static bending test methods of wood using todomatsu (Japanese fir)

We examined the methods of measuring the bending properties of wood using todomatsu (Abies sachalinensis Fr. Schmidt) by elementary bending theory. Three- and four-point bending tests were conducted under various span/depth ratios, and the load, deflection, loading point displacement, and strain at the bottom of the center were simultaneously measured. The load-deflection, load-loading point displacement, and load-strain relations were regressed into Ramberg-Osgood's function. Young's modulus, proportional limit stress, and bending strength were calculated by substituting the parameters obtained by the regression into the equations derived from elementary bending theory. By comparing the obtained properties with each other, we examined an appropriate method for measuring the bending properties based on elementary bending theory. The results are summarized as follows: 1) regarding the measurement of Young's modulus, a strain gauge was effective for reducing the influence of span/depth ratio even in the small span/depth ratio range; when the strain gauge was not used, the four-point bending test with measuring the deflection at the center was most effective because the span/depth ratio range where Young's modulus was stably obtained was larger than those obtained from the other methods. ; 2) the proportional limit stress was greatly influenced by the method of measuring deflection, and, in contrast, the influence of span/depth ratio on the proportional limit stress was less significant than that on Young's modulus; 3) the influence of span/depth ratio on the bending strength was less significant than that on Young's modulus; and 4) the load-deflection relation under four-point bending using a specimen whose span/depth ratio is larger than 20 is recommended for consistent determination of the bending properties based on elementary bending theory.
Sebaceous-immunobiology is orchestrated by sebum lipids

ABSTRACT The major role of sebaceous glands in mammals is to produce sebum, which coats the epidermis and the hair providing waterproofing, thermoregulation and photoprotection. However, as the need for these functions decreased along the evolutionary changes in humans, a relevant question has been raised: are sebaceous glands and sebum the remnants of our mammalian heritage or do they have overtaken a far more complex role in human skin biology? Trying to provide answers to this question, this review introduces the evolving field of sebaceous immunobiology and puts into the focus the pathways that sebum lipids use to influence the immune milieu of the skin. By introducing possible modifiers of sebaceous lipogenesis and discussing the – human-specific – alterations in composition and amount of sebum, the attribute of sebum as a sensitive tool, which is capable of translating multiple signalling pathways into the dermal micro environment is presented. Further their interaction with macrophages and keratinocytes involves sebum lipid fractions into disease pathogenesis, which could lead – on the other side – to the development of novel sebum-based therapeutic strategies.
Application of diffusional kurtosis imaging to detect occult brain damage in multiple sclerosis and neuromyelitis optica

Multiple sclerosis (MS) and neuromyelitis optica (NMO) are two common types of inflammatory demyelinating disease of the central nervous system. Early distinction of NMO from MS is crucial but quite challenging. In this study, 13 NMO spectrum disorder patients (Expanded Disability Status Scale (EDSS) of 3.0 ± 1.7, ranging from 2 to 6.5; disease duration of 5.3 ± 4.7 years), 17 relapsing–remitting MS patients (EDSS of 2.6 ± 1.4, ranging from 1 to 5.5; disease duration of 7.9 ± 7.8 years) and 18 healthy volunteers were recruited. Diffusional kurtosis imaging was employed to discriminate NMO and MS patients at the early or stable stage from each other, and from healthy volunteers. The presence of alterations in diffusion and diffusional kurtosis metrics in normal‐appearing white matter (NAWM) and diffusely increased mean diffusivity (MD) in the cortical normal‐appearing gray matter (NAGM) favors the diagnosis of MS rather than NMO. Meanwhile, normal diffusivities and kurtosis metrics in all NAWM as well as increases in MD in the frontal and temporal NAGM suggest NMO. Our results suggest that diffusion and diffusional kurtosis metrics may well aid in discriminating the two diseases.
First‐line treatment selection and early monitoring patterns in chronic phase‐chronic myeloid leukemia in routine clinical practice: SIMPLICITY

Achieving successful outcomes in chronic phase‐chronic myeloid leukemia (CP‐CML) requires careful monitoring of cytogenetic/molecular responses (CyR/MR). SIMPLICITY (NCT01244750) is an observational study exploring tyrosine kinase inhibitor use and management patterns in patients with CP‐CML receiving first‐line imatinib (n = 416), dasatinib (n = 418) or nilotinib (n = 408) in the US and 6 European countries in routine clinical practice. Twelve‐month follow‐up data of 1242 prospective patients (enrolled October 01 2010‐September 02 2015) are reported. 81% of patients had baseline comorbidities. Treatment selection was based on perceived efficacy over patient comorbidity profile. There was a predominance of imatinib‐treated patients enrolled earlier in the study, with subsequent shift toward dasatinib‐ and nilotinib‐treated patients by 2013/2014. Monitoring for either CyR/MR improved over time and was documented for 36%, 82%, and 95% of patients by 3, 6, and 12 months, respectively; 5% had no documentation of CyR/MR monitoring during the first year of therapy. Documentation of MR/CyR testing was higher in Europe than the US (P < .001) and at academic versus community practices (P = .001). Age <65 years, patients being followed at sites within Europe, those followed at academic centers and patients no longer on first‐line therapy were more likely to be monitored by 12 months. SIMPLICITY demonstrates that the NCCN and ELN recommendations on response monitoring have not been consistently translated into routine clinical practice. In the absence of appropriate monitoring practices, clinical response to TKI therapy cannot be established, any needed changes to treatment strategy will thus not be implemented, and long‐term patient outcomes are likely to be impacted.
Numerical models of salt marsh evolution: Ecological, geomorphic, and climatic factors

Salt marshes are delicate landforms at the boundary between the sea and land. These ecosystems support a diverse biota that modifies the erosive characteristics of the substrate and mediates sediment transport processes. Here we present a broad overview of recent numerical models that quantify the formation and evolution of salt marshes under different physical and ecological drivers. In particular, we focus on the coupling between geomorphological and ecological processes and on how these feedbacks are included in predictive models of landform evolution. We describe in detail models that simulate fluxes of water, organic matter, and sediments in salt marshes. The interplay between biological and morphological processes often produces a distinct scarp between salt marshes and tidal flats. Numerical models can capture the dynamics of this boundary and the progradation or regression of the marsh in time. Tidal channels are also key features of the marsh landscape, flooding and draining the marsh platform and providing a source of sediments and nutrients to the marsh ecosystem. In recent years, several numerical models have been developed to describe the morphogenesis and long‐term dynamics of salt marsh channels. Finally, salt marshes are highly sensitive to the effects of long‐term climatic change. We therefore discuss in detail how numerical models have been used to determine salt marsh survival under different scenarios of sea level rise.
Atypical Femoral Shaft Fractures in Female Bisphosphonate Users Were Associated with an Increased Anterolateral Femoral Bow and a Thicker Lateral Cortex: A Case-Control Study

The purpose of our study was to investigate the radiographic characteristics of atypical femoral shaft fractures (AFSFs) in females with a particular focus on femoral bow and cortical thickness. We performed a fracture location-, age-, gender-, and ethnicity-matched case-control study. Forty-two AFSFs in 29 patients and 22 typical osteoporotic femoral shaft fractures in 22 patients were enrolled in AFSF group and control group, respectively. With comparing demographics between two groups, radiographically measured femoral bow and cortical thicknesses of AFSF group were compared with control group. All AFSF patients were females with a mean age of 74.4 years (range, 58–85 years). All had a history of bisphosphonate (BP) use with a mean duration of 7.3 years (range 1–17 years). Femoral bow of AFSF group was significantly higher than control group on both anteroposterior (AP) and lateral radiographs after age correction. Mean femoral bow on an AP radiograph was 12.39° ± 5.38° in AFSF group and 3.97 ± 3.62° in control group (P < 0.0001). Mean femoral bow on the lateral radiograph was 15.71° ± 5.62° in AFSF group and 10.72° ± 4.61° in control group (after age correction P = 0.003). And cortical thicknesses of AFSF group demonstrated marked disparity between tensile and compressive side of bowed femurs in this study. An adjusted lateral cortical thickness was 10.5 ± 1.4 mm in AFSF group and 8.1 ± 1.3 mm in control group (after age correction P < 0.0001) while medial cortical thickness of AFSF group was not statistically different from control group. Correlation analysis showed that the lateral femoral bow on the AP radiograph was solely related to lateral CTI (R = 0.378, P = 0.002). AFSFs in female BP users were associated with an increased anterolateral femoral bow and a thicker lateral cortex of femurs.
HiCH

The Internet of Things (IoT) paradigm holds significant promises for remote health monitoring systems. Due to their life- or mission-critical nature, these systems need to provide a high level of availability and accuracy. On the one hand, centralized cloud-based IoT systems lack reliability, punctuality and availability (e.g., in case of slow or unreliable Internet connection), and on the other hand, fully outsourcing data analytics to the edge of the network can result in diminished level of accuracy and adaptability due to the limited computational capacity in edge nodes. In this paper, we tackle these issues by proposing a hierarchical computing architecture, HiCH, for IoT-based health monitoring systems. The core components of the proposed system are 1) a novel computing architecture suitable for hierarchical partitioning and execution of machine learning based data analytics, 2) a closed-loop management technique capable of autonomous system adjustments with respect to patient’s condition. HiCH benefits from the features offered by both fog and cloud computing and introduces a tailored management methodology for healthcare IoT systems. We demonstrate the efficacy of HiCH via a comprehensive performance assessment and evaluation on a continuous remote health monitoring case study focusing on arrhythmia detection for patients suffering from CardioVascular Diseases (CVDs).
Czech Grammar Agreement Dataset for Evaluation of Language Models

AGREE is a dataset and task for evaluation of language models based on grammar agreement in Czech. The dataset consists of sentences with marked suffixes of past tense verbs. The task is to choose the right verb suffix which depends on gender, number and animacy of subject. It is challenging for language models because 1) Czech is morphologically rich, 2) it has relatively free word order, 3) high out-of-vocabulary (OOV) ratio, 4) predicate and subject can be far from each other, 5) subjects can be unexpressed and 6) various semantic rules may apply. The task provides a straightforward and easily reproducible way of evaluating language models on a morphologically rich language.