Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Aging Stability of Ethylene-Norbornene Composites Filled with Lawsone-Based Hybrid Pigment

In this study, we produced a new organic-inorganic hybrid pigment based on a natural chromophore. Lawsone was selected as the active organic compound and incorporated into aluminum-magnesium hydroxycarbonate (LH). The hydroxynaphthoquinone derivative lawsone (Lawsonia inermis L.) is a naturally occurring dye, which is commonly used as a colorant because of its nontoxicity and biological functions. The structure and stability of the hybrid colorant were investigated using 27-Al solid-state nuclear magnetic resonance (NMR) spectroscopy, X-ray diffraction (XRD), secondary ion mass spectrometry (TOF-SIMS), thermogravimetric analysis (TGA), scanning electron microscopy (SEM) and UV-Vis spectroscopy. TOF-SIMS and 27Al NMR spectroscopy revealed interactions between the dye molecules and metal ions present in the LH host, confirming successful formation of an LH-based hybrid (LH/lawsone). In the next part of the study, we examined the effect of the hybrid pigment on the mechanical and thermal properties of ethylene-norbornene (EN) materials, as well as the aging resistance of the colored composites to irradiation across the full solar spectrum. Dynamic mechanical analysis (DMA) and the results of tensile break tests revealed that the EN+LH/lawsone composite had significantly better resistance to solar irradiation in comparison to EN and EN with an unmodified carrier.
Bone Augmentation and Simultaneous Implant Placement with Allogenic Bone Rings and Analysis of Its Purification Success

The main objective of this manuscript was to demonstrate the use of freeze-dried bone allografts (FDBA) by means of a technique of simultaneous bone augmentation and implant placement (“Bone Ring Technique”) in different indications, i.e., ridge reconstruction and sinus floor elevation procedure with a maxillary bone height of less than 4 mm. Moreover, cases with an up to 3-year follow-up were chosen to analyze the techniques of mid-term clinical success. Finally, the purification success of the FDBA was analyzed by means of established scanning electron microscopic (SEM) and histological methods. The FBDA bone ring was applied in three different patients and indications and presented; the healing success was analyzed on the basis of radiographical and clinical images. For analysis of the purification of the allogeneic bone, previously established histological methods and scanning electron microscopy (SEM) were applied. All analyzed patient cases showed that the FDBA-based bone ring was fully integrated into newly built alveolar bone. Furthermore, the observations revealed that the three-dimensional bone reconstructions in maxilla and mandible were stable within the observational period of up to 3 years. Altogether, the present data show that the application of the Bone Ring Technique using the FDBA rings allows for successful regeneration of alveolar bone with a predictable clinical outcome, functionality and esthetics. Moreover, the material analyses showed that the allogeneic bone tissue was free of cells or cell remnants, while the (ultra-) structure of the bone matrix has been retained. Thus, the biological safety of the FDBA has been confirmed.
Evaluation of Phage Therapy in the Context of Enterococcus faecalis and Its Associated Diseases

Bacteriophages (phages) or bacterial viruses have been proposed as natural antimicrobial agents to fight against antibiotic-resistant bacteria associated with human infections. Enterococcus faecalis is a gut commensal, which is occasionally found in the mouth and vaginal tract, and does not usually cause clinical problems. However, it can spread to other areas of the body and cause life-threatening infections, such as septicemia, endocarditis, or meningitis, in immunocompromised hosts. Although E. faecalis phage cocktails are not commercially available within the EU or USA, there is an accumulated evidence from in vitro and in vivo studies that have shown phage efficacy, which supports the idea of applying phage therapy to overcome infections associated with E. faecalis. In this review, we discuss the potency of bacteriophages in controlling E. faecalis, in both in vitro and in vivo scenarios. E. faecalis associated bacteriophages were compared at the genome level and an attempt was made to categorize phages with respect to their suitability for therapeutic application, using orthocluster analysis. In addition, E. faecalis phages have been examined for the presence of antibiotic-resistant genes, to ensure their safe use in clinical conditions. Finally, the domain architecture of E. faecalis phage-encoded endolysins are discussed.
A Complete Survey of Glycoalkaloids Using LC-FTICR-MS and IRMPD in a Commercial Variety and a Local Landrace of Eggplant (Solanum melongena L.) and their Anticholinesterase and Antioxidant Activities

Eggplant contains glycoalkaloids (GAs), a class of nitrogen-containing secondary metabolites of great structural variety that may have both adverse and beneficial biological effects. In this study, we performed a complete survey of GAs and their malonylated form, in two genotypes of eggplants: A commercial cultivated type, Mirabella (Mir), with purple peel and bitter taste and a local landrace, named Melanzana Bianca di Senise (Sen), characterized by white peel with purple strip and a typical sweet aroma. Besides the analysis of their morphological traits, nineteen glycoalkaloids were tentatively identified in eggplant berry extracts based upon LC-ESI-FTICR-MS analysis using retention times, elution orders, high-resolution mass spectra, as well as high-resolution fragmentation by IRMPD. The relative signal intensities (i.e., ion counts) of the GAs identified in Mir and Sen pulp extracts showed as solamargine, and its isomers are the most abundant. In addition, anticholinesterase and antioxidant activities of the extracts were evaluated. Pulp tissue was found to be more active in inhibiting acetylcholinesterase enzyme than peel showing an inhibitory effect higher than 20% for Mir pulp. The identification of new malonylated GAs in eggplant is proposed.
Lying Postures of Dairy Cows in Cubicles and on Pasture

Simple Summary Cows housed indoors with cubicles are probably more restricted in their choice of lying posture and orientation compared with cows housed on pasture. We therefore studied lying postures on pasture in Uruguay and the Netherlands, and in cubicles in the Netherlands, also recording orientation on pasture in Uruguay and divider and bedding type in Dutch cubicles. Cows on pasture in Uruguay showed more long postures, lying on their belly with the neck stretched, and, per herd, cows preferred a specific lying orientation. Dutch cows on pasture showed more wide postures, lying on their side with three legs stretched, while in cubicles they showed more narrow postures, lying on their side with folded hind legs. More long and less short postures were seen in cubicles with soft floors and English dividers; more narrow postures were seen in cubicles with concrete floors. Wide postures were seen more in cubicles with mattresses and free-hanging dividers. We conclude that since cows in cubicles show more narrow postures than on pasture and cannot choose lying orientation, their choice in showing preferred behavior is restricted. More research is needed to study the consequences of restricted choice in lying behavior on the health and welfare of dairy cows. Abstract Cows housed indoors with cubicles are probably more restricted in their choice of lying posture and orientation compared with cows housed on pasture. We therefore compared lying postures on pasture in Uruguay and the Netherlands with lying postures in cubicles in the Netherlands, also recording orientation on pasture in Uruguay and divider and bedding type in Dutch cubicles. We visited one farm with four herds in Uruguay, doing live observations, and 25 Dutch farms, taking pictures of cows. Observations of 205 cows on pasture in Uruguay showed more long postures, lying on their belly with their neck stretched. Two herds preferred lying towards north and south, while one herd preferred west and east. Pictures of 217 cows on pasture in the Netherlands showed more wide postures (lying on the side with three or four legs stretched out). Pictures of 527 cows in cubicles in the Netherlands showed more narrow postures (lying on the side with hind legs folded). More long postures (lying on the belly with a stretched neck) and less short postures (lying with the head folded back) were seen in cubicles with soft floors and English dividers; more narrow postures were seen in cubicles with concrete floors. Wide postures were seen more in cubicles with mattresses and free-hanging dividers. We conclude that since cows in cubicles show more narrow postures than on pasture and cannot choose their orientation, their choice in showing preferred behavior is restricted. More research is needed to study the consequences of restricted choice in lying behavior on the health and welfare of dairy cows.
Estimation of Air Damping in Out-of-Plane Comb-Drive Actuators

The development of new compliant resonant microsystems and the trend towards further miniaturization have recently raised the issue of the accuracy and reliability of computational tools for the estimation of fluid damping. Focusing on electrostatically actuated torsional micro-mirrors, a major dissipation contribution is linked to the constrained flow of air at comb fingers. In the case of large tilting angles of the mirror plate, within a period of oscillation the geometry of the air domain at comb-drives gets largely distorted, and the dissipation mechanism is thereby affected. In this communication, we provide an appraisal of simple analytical solutions to estimate the dissipation in the ideal case of air flow between infinite plates, at atmospheric pressure. The results of numerical simulations are also reported to assess the effect on damping of the finite size of actual geometries.
Privacy-Preserving Back Propagation Neural Network Learning In Signature Scheme

Cloud computing allows their clients to share data. Multiple parties may join through conducting joint Back propagation neural network learning on the union of their respective data sets. During this process no party wants to disclose her/his private data to others. Existing schemes supporting this kind of collaborative learning are either limited in the way of data partition or just consider two parties. There lacks a solution that allows two or more parties, each with an arbitrarily partitioned data set, to join conduct the learning. This paper solves this open problem by utilizing the power of cloud computing. In our proposed scheme, each party encrypts his/her private data locally and uploads the cipher texts into the cloud. The cloud then executes most of the operations over cipher texts without knowing the original private data. Each participants have their own login id to see their report in cloud. To connect with Cloud user must give their username and password then only they can able to connect the server. Here the users are able to view their own details efficiently.
Probing the in situ Elastic Nonlinearity of Rocks with Earth Tides and Seismic Noise.

Heterogeneous materials such as rocks, concrete, and granular materials exhibit a strong elastic nonlinearity. The sensitivity of the elastic nonlinearity to the applied stress and pore pressure in principle allows the use of seismic waves for remote observations of stress or pore pressure changes. Yet the nonlinearity of rocks is difficult to quantify in situ as active deformation tests are not possible in the field. We investigate the elastic nonlinearity in a fully natural experiment using the ambient seismic noise of a single seismic station to sense changes of the seismic velocity in the subsurface reaching 0.026% in response to the minute deformation caused by various constituents of the tidal forces exerted by the Sun and Moon.
A randomized controlled trial of a wearable technology‐based intervention for increasing moderate to vigorous physical activity and reducing sedentary behavior in breast cancer survivors: The ACTIVATE Trial

The benefits of an active lifestyle after a breast cancer diagnosis are well recognized, but the majority of survivors are insufficiently active. The ACTIVATE Trial examined the efficacy of an intervention (use of the Garmin Vivofit 2 activity monitor coupled with a behavioral feedback and goal‐setting session and 5 telephone‐delivered health coaching sessions) to increase moderate to vigorous physical activity (MVPA) and reduce sedentary behavior in breast cancer survivors.
Estimating Forces of Robotic Pouring Using a LSTM RNN

In machine learning, it is very important for a robot to be able to estimate dynamics from sequences of input data. This problem can be solved using a recurrent neural network. In this paper, we will discuss the preprocessing of 10 states of the dataset, then the use of a LSTM recurrent neural network to estimate one output state (dynamics) from the other 9 input states. We will discuss the architecture of the recurrent neural network, the data collection and preprocessing, the loss function, the results of the test data, and the discussion of changes that could improve the network. The results of this paper will be used for artificial intelligence research and identify the capabilities of a LSTM recurrent neural network architecture to estimate dynamics of a system.
Concepts of Programming Languages: A Unified Approach

class Number virtual instance methods: sum: Number -> Number difference: Number -> Number product: Number -> Number instance methods: sqr() = product(self) end class Figure 20.5: Class Number with virtual methods. The sqr method can use product, even though product is not defined here. The class is abstract to indicate that it has at least one virtual method. the derivative, the derivative method is virtual, and the methods for each kind of data are placed with that kind of data, in its class. When a single type with variants is used instead, as done in Chapter 14, adding a new kind of expression requires modifying functions by adding a new case to each that handles the new kind of expression. But the object-oriented approach avoids that. Adding a new kind of expression just requires adding a new subclass of Expression and defining the virtual methods for that class. There is no need to modify any existing classes or methods at all. Now imagine providing expressions and symbolic computation on them in a library. Keep in mind that most programmers are not allowed to modify the library, but can only use it. The single-type approach allows the writer of the library to include a fixed collection of expression forms, but does not allow anyone else to add new expressions. Classes and virtual methods allow anyone to add new kinds of expressions in his or her program without modifying the library at all. Sometimes you do not want to add a new variation but to remove one because it is no longer needed. That is also easy to achieve using the object-oriented approach; you just remove the subclass that implements that variation (and any place where constructors of that subclass are used). There is no need to modify the implementations of other classes. 20.6. 3. Virtual methods as function parameters Some programming languages allow you to pass functions as parameters to other functions, but most object-oriented languages do not allow you to do that. But sometimes you can simulate function parameters by using virtual methods. Suppose that you want a function or method, time(f), that runs another function f and tells you how long f takes to run. In an object-oriented programming language, you create a class called Timer, as in Figure 20.6, containing a virtual method called run that represents the function that is to be timed. It is a hook where the actual function can be attached. To time a function, you define a subclass of Timer where the run method runs the desired function. Instead of asking one object to time the execution of a method in another object, you let the subclass inherit the time method, so an object of the subclass knows how to time itself. Chapter 10 showed that the ability to pass functions as parameters to other functions allows the creation of versatile libraries containing functions that implement entire classes of algorithms. Virtual methods in class libraries can be used to achieve similar generality.
Wearable-Based Mobile Health App in Gastric Cancer Patients for Postoperative Physical Activity Monitoring: Focus Group Study

Background Surgical cancer patients often have deteriorated physical activity (PA), which in turn, contributes to poor outcomes and early recurrence of cancer. Mobile health (mHealth) platforms are progressively used for monitoring clinical conditions in medical subjects. Despite prevalent enthusiasm for the use of mHealth, limited studies have applied these platforms to surgical patients who are in much need of care because of acutely significant loss of physical function during the postoperative period. Objective The aim of our study was to determine the feasibility and clinical value of using 1 wearable device connected with the mHealth platform to record PA among patients with gastric cancer (GC) who had undergone gastrectomy. Methods We enrolled surgical GC patients during their inpatient stay and trained them to use the app and wearable device, enabling them to automatically monitor their walking steps. The patients continued to transmit data until postoperative day 28. The primary aim of this study was to validate the feasibility of this system, which was defined as the proportion of participants using each element of the system (wearing the device and uploading step counts) for at least 70% of the 28-day study. “Definitely feasible,” “possibly feasible,” and “not feasible” were defined as ≥70%, 50%-69%, and <50% of participants meeting the criteria, respectively. Moreover, the secondary aim was to evaluate the clinical value of measuring walking steps by examining whether they were associated with early discharge (length of hospital stay <9 days). Results We enrolled 43 GC inpatients for the analysis. The weekly submission rate at the first, second, third, and fourth week was 100%, 93%, 91%, and 86%, respectively. The overall daily submission rate was 95.5% (1150 days, with 43 subjects submitting data for 28 days). These data showed that this system met the definition of “definitely feasible. ” Of the 54 missed transmission days, 6 occurred in week 2, 12 occurred in week 3, and 36 occurred in week 4. The primary reason for not sending data was that patients or caregivers forgot to charge the wearable devices (>90%). Furthermore, we used a multivariable-adjusted model to predict early discharge, which demonstrated that every 1000-step increment of walking on postoperative day 5 was associated with early discharge (odds ratio 2.72, 95% CI 1.17-6.32; P=.02). Conclusions Incorporating the use of mobile phone apps with wearable devices to record PA in patients of postoperative GC was feasible in patients undergoing gastrectomy in this study. With the support of the mHealth platform, this app offers seamless tracing of patients’ recovery with a little extra burden and turns subjective PA into an objective, measurable parameter.
How Confidence in Prior Attitudes, Social Tag Popularity, and Source Credibility Shape Confirmation Bias Toward Antidepressants and Psychotherapy in a Representative German Sample: Randomized Controlled Web-Based Study

Background In health-related, Web-based information search, people should select information in line with expert (vs nonexpert) information, independent of their prior attitudes and consequent confirmation bias. Objective This study aimed to investigate confirmation bias in mental health–related information search, particularly (1) if high confidence worsens confirmation bias, (2) if social tags eliminate the influence of prior attitudes, and (3) if people successfully distinguish high and low source credibility. Methods In total, 520 participants of a representative sample of the German Web-based population were recruited via a panel company. Among them, 48.1% (250/520) participants completed the fully automated study. Participants provided prior attitudes about antidepressants and psychotherapy. We manipulated (1) confidence in prior attitudes when participants searched for blog posts about the treatment of depression, (2) tag popularity —either psychotherapy or antidepressant tags were more popular, and (3) source credibility with banners indicating high or low expertise of the tagging community. We measured tag and blog post selection, and treatment efficacy ratings after navigation. Results Tag popularity predicted the proportion of selected antidepressant tags (beta=.44, SE 0.11; P<.001) and blog posts (beta=.46, SE 0.11; P<.001). When confidence was low (−1 SD), participants selected more blog posts consistent with prior attitudes (beta=−.26, SE 0.05; P<.001). Moreover, when confidence was low (−1 SD) and source credibility was high (+1 SD), the efficacy ratings of attitude-consistent treatments increased (beta=.34, SE 0.13; P=.01). Conclusions We found correlational support for defense motivation account underlying confirmation bias in the mental health–related search context. That is, participants tended to select information that supported their prior attitudes, which is not in line with the current scientific evidence. Implications for presenting persuasive Web-based information are also discussed. Trial Registration ClinicalTrials.gov NCT03899168; https://clinicaltrials.gov/ct2/show/NCT03899168 (Archived by WebCite at http://www.webcitation.org/77Nyot3Do)
Identification of intrinsic long-range degree correlations in complex networks

Many real-world networks exhibit degree-degree correlations between nodes separated by more than one step. Such long-range degree correlations (LRDCs) can be fully described by one joint and four conditional probability distributions with respect to degrees of two randomly chosen nodes and shortest path distance between them. While LRDCs are induced by nearest-neighbor degree correlations (NNDCs) between adjacent nodes, some networks possess intrinsic LRDCs which cannot be generated by NNDCs. Here we develop a method to extract intrinsic LRDC in a correlated network by comparing the probability distributions for the given network with those for nearest-neighbor correlated random networks. We also demonstrate the utility of our method by applying it to several real-world networks.
Monte-Carlo Tree Search for Efficient Visually Guided Rearrangement Planning

We address the problem of visually guided rearrangement planning with many movable objects, i.e., finding a sequence of actions to move a set of objects from an initial arrangement to a desired one, while relying on visual inputs coming from an RGB camera. To do so, we introduce a complete pipeline relying on two key contributions. First, we introduce an efficient and scalable rearrangement planning method, based on a Monte-Carlo Tree Search exploration strategy. We demonstrate that because of its good trade-off between exploration and exploitation our method (i) scales well with the number of objects while (ii) finding solutions which require a smaller number of moves compared to the other state-of-the-art approaches. Note that on the contrary to many approaches, we do not require any buffer space to be available. Second, to precisely localize movable objects in the scene, we develop an integrated approach for robust multi-object workspace state estimation from a single uncalibrated RGB camera using a deep neural network trained only with synthetic data. We validate our multi-object visually guided manipulation pipeline with several experiments on a real UR-5 robotic arm by solving various rearrangement planning instances, requiring only 60 ms to compute the plan to rearrange 25 objects. In addition, we show that our system is insensitive to camera movements and can successfully recover from external perturbations.