Miracle-dz/UniFAR-FTUs huggingface dataset:
PAMAM dendrimer roles in gene delivery methods and stem cell research

Nanotechnology has provided new technological opportunities, which could help in challenges confronting stem cell research. Polyamidoamine (PAMAM) dendrimers, a new class of macromolecular polymers with high molecular uniformity, narrow molecular distribution specific size and shape and highly functionalised terminal surface have been extensively explored for biomedical application. PAMAM dendrimers are also nanospherical, hyperbranched and monodispersive molecules exhibiting exclusive properties which make them potential carriers for drug and gene delivery.
The Effect of Offset Correction and Cursor on Mid-Air Pointing in Real and Virtual Environments

Pointing at remote objects to direct others' attention is a fundamental human ability. Previous work explored methods for remote pointing to select targets. Absolute pointing techniques that cast a ray from the user to a target are affected by humans' limited pointing accuracy. Recent work suggests that accuracy can be improved by compensating systematic offsets between targets a user aims at and rays cast from the user to the target. In this paper, we investigate mid-air pointing in the real world and virtual reality. Through a pointing study, we model the offsets to improve pointing accuracy and show that being in a virtual environment affects how users point at targets. In the second study, we validate the developed model and analyze the effect of compensating systematic offsets. We show that the provided model can significantly improve pointing accuracy when no cursor is provided. We further show that a cursor improves pointing accuracy but also increases the selection time.
A new validation index for fuzzy clustering and its comparisons with other methods

This paper presents a new validation index for the Fuzzy C-Means algorithm, which is composed of two metrics, the modified partition entropy index and the sum of the distances between the means of the fuzzy partitions. The modified partition entropy represents the variation of the data in clusters of the dataset, and the sum of the distances between the means of the fuzzy partition represents the separation between clusters in the data set. The proposed index was tested with synthetic and benchmark datasets with good results.
Executable C++ program generation from the structured object-oriented design diagrams

The paper describes a system for generating an executable C++ program from object oriented design diagrams. Especially an event trace diagram and a decision table are used to describe an operational definition. The decision table offers a high level language LOLA for the brief expression of controls that are dependent on the data structure. This language allows the methods to be expressed easily, briefly, and visually. A C++ program was generated from these diagrams in such a way that the part cliches are edited to satisfy LOLA expression and embedded into the frame cliche representing the skeleton of the whole program.
Estimation of Progesterone in Oil based Injection by UV- Visible Spectroscopy.

Progesterone is steroidal hormone belongs to class of Progestogens. Progesterone is widely used for hormone replacement therapy. Literature reveals various chromatographic methods for the detection of progesterone in combination with various other steroidal drugs. Therefore it is necessary to develop method for rapid, simple and accurate method for estimation of progesterone as single component from oil based injection was elaborated. In proposed method calibration curve was obtained with correlation coefficient, 0.996. 2Propanol was found to be suitable solvent for extraction of progesterone from oil based injection. UV detection was carried out at 244nm. Developed method was validated for precision, accuracy and linearity.
Hernandezine, a novel AMPK activator induces autophagic cell death in drug-resistant cancers

Drug resistance hinder most cancer chemotherapies and leads to disease recurrence and poor survival of patients. Resistance of cancer cells towards apoptosis is the major cause of these symptomatic behaviours. Here, we showed that isoquinoline alkaloids, including liensinine, isoliensinine, dauricine, cepharanthine and hernandezine, putatively induce cytotoxicity against a repertoire of cancer cell lines (HeLa, A549, MCF-7, PC3, HepG2, Hep3B and H1299). Proven by the use of apoptosis-resistant cellular models and autophagic assays, such isoquinoline alkaloid-induced cytotoxic effect involves energy- and autophagy-related gene 7 (Atg7)-dependent autophagy that resulted from direct activation of AMP activated protein kinase (AMPK). Hernandezine possess the highest efficacy in provoking such cell death when compared with other examined compounds. We confirmed that isoquinoline alkaloid is structurally varied from the existing direct AMPK activators. In conclusion, isoquinoline alkaloid is a new class of compound that induce autophagic cell death in drug-resistant fibroblasts or cancers by exhibiting its direct activation on AMPK.
AQM scheme design for TCP network via Takagi-Sugeno fuzzy method

This paper proposes a novel T-S fuzzy control method instead of the traditional linear system control method to improve the TCP network performance. Thus a TCP network can be modeled as a T-S fuzzy system, and by use of linear matrix inequality method and cone complementarity linearization algorithm, a fuzzy state feedback controller is provided while considering the problem of the asynchronous membership grades between the controller and the plant. Simulation results are presented to show that the proposed control approach can guarantee the asymptotical stability of the studied system and the desired queue size. © 2016 Wiley Periodicals, Inc. Complexity 21: 606–612, 2016
Adaptive output regulation of nonlinear systems described by multiple linear models

Abstract In this paper the output regulation problem for nonlinear systems described by multiple linear models with unknown parameters is considered. Based on the Lyapunov stability theory, an adaptive controller which stabilize the system is derived. Then sufficient conditions for the output regulation problem with full information to be solvable are established. Simulation results are given to illustrate the theory.
Guided bone tissue regeneration using a hollow calcium phosphate based implant in a critical size rabbit radius defect

Long bone fractures are common and sometimes difficult to treat. Autologous bone (AB), bovine bone and calcium phosphates are used to stimulate bone growth with varying results. In the present study, a calcium phosphate cement (CPC) that previously showed promising grafting capabilities was evaluated for the first time in a long bone defect. A radius defect of 20 mm was created in 20 rabbits. The defect was filled by either a hollow CPC implant that had been manufactured as a replica of a rabbit radius through indirect 3D printing, or by particulate AB as control. Defect filling and bone formation was evaluated after 12 weeks by combining micro computed tomography (μCT) and scoring of 3D images, together with histomorphometry and histology. The μCT and histomorphometric evaluations showed a similar amount of filling of the defect (combining graft and bone) between the CPC and AB group, but the scoring of 3D images showed that the filling in the CPC group was significantly larger. Histologically the AB graft could not be distinguished from the new bone. The AB treated defects were found to be composed of more bone than the CPC group, including reorganised cancellous and cortical bone. Both the CPC and AB material was associated with new bone formation, also in the middle of the defect, which could result in closing of the otherwise critically sized gap. This study shows the potential for an indirectly 3D printed implant in guided bone regeneration in critically sized long bone defects.
60 GHz High Data Rate Wireless Communication System

This paper presents the design and the realization of a 60 GHz wireless Gigabit Ethernet communication system. A differential encoded binary phase shift keying modulation (DBPSK) and differential demodulation schemes are adopted for the IF blocks. The Gigabit Ethernet interface allows a high speed transfer of multimedia files via a 60 GHz wireless link. First measurement results are shown for 875 Mbps data rate.
Nanomaterials for biomedical applications.

Recent advances in creating nanomaterials have created new opportunities in biomedical research and clinical applications [1,2]. High-quality nanomaterials, of well-controlled size and shape, are a new class of building blocks to enable the establishment of assays for monitoring molecular signals in biological systems and living organisms. Many of these new nanoassays have higher sensitivity, selectivity and throughput than conventional bioanalytical methods. On the one hand, these nanoassays will be capable of detecting biochemical changes at the single-molecule level in living cells [3]. Conversely, these assays will lead to low-cost, point-of-care devices for rapid diagnosis of pathogenic and genetic diseases (e.g., HIV and cancer) [4]. In addition, nanomaterials have been used as advanced contrast agents for clinical imaging technologies, such as MRI, computer tomography and ultrasound [5–7]. Moreover, the use of nanomaterials will lead to the invention of ‘smart’ drug-delivery vehicles, new therapies and even new scalpel-free surgery methods. These new opportunities stem primarily from the novel nature of nanomaterials. Owing to their size-dependent effects, nanomaterials exhibit new physical and chemical properties compared with conventional bulk and molecular materials [8]. In general, nanomaterials include inorganic, organic and inorganic/organic composite nanostructures, such as nanoparticles, nanowires and nanopatterns. This special issue of Nanomedicine presents readers with current exciting developments in the use of nanoparticles and nanopatterns for biomedical diagnosis and drug delivery.
Channel Estimation and Performance Analysis of One-Bit Massive MIMO Systems

This paper considers channel estimation and system performance for the uplink of a single-cell massive multiple-input multiple-output system. Each receiver antenna of the base station is assumed to be equipped with a pair of one-bit analog-to-digital converters to quantize the real and imaginary part of the received signal. We first propose an approach for channel estimation that is applicable for both flat and frequency-selective fading, based on the Bussgang decomposition that reformulates the nonlinear quantizer as a linear function with identical first- and second-order statistics. The resulting channel estimator outperforms previously proposed approaches across all SNRs. We then derive closed-form expressions for the achievable rate in flat fading channels assuming low SNR and a large number of users for the maximal ratio and zero forcing receivers that takes channel estimation error due to both noise and one-bit quantization into account. The closed-form expressions, in turn, allow us to obtain insight into important system design issues such as optimal resource allocation, maximal sum spectral efficiency, overall energy efficiency, and number of antennas. Numerical results are presented to verify our analytical results and demonstrate the benefit of optimizing system performance accordingly.
Practical Infrared Visual Odometry

The use of cameras as a sensor for odometry estimation is an active research topic that has seen significant growth in recent years. Most methods, however, are only suitable for standard cameras that rely on reasonable lighting. An alternative to overcome low-light conditions is the use of thermal or long-wave infrared imaging. Although visible spectrum and thermal imaging share many characteristics, it is not straightforward to apply standard visual odometry algorithms to thermal imaging data. In this paper, we propose a practical visual odometry system based on a monocular thermal camera. As monocular odometry suffers from an unknown scale factor, the system performs efficient ground plane detection for targeted feature extraction, such that the scale factor can be reliably estimated if the camera height and pitch are known. We also address the problem of periodic nonuniformity correction, which is a necessary characteristic of thermal cameras that freezes the output potentially for over a second and can severely affect motion estimation. In this sense, we automatically determine appropriate times to perform nonuniformity correction based on the current and predicted camera rotations. Experiments illustrate the applicability of the system and compare it with other state estimation approaches.
Enabling electrospinning of medium-chain length polyhydroxyalkanoates (PHAs) by blending with short-chain length PHAs

Abstract Polyhydroxyalkanoates (PHAs) have recently attracted significant attention in medical applications. Electrospinning of short chain-length (scl-)PHAs has been extensively investigated, while medium chain length (mcl-)PHAs are not suitable for electrospinning since they are elastomeric at room temperature. We improved the electrospinability of an mcl-PHA poly (3-hydroxyoctanoate-co-3-hydroxyhexanoate) (PHOHHx) by blending with a scl-PHA poly (3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV25, with 25 mol% HV). Morphology of electrospun PHBV25/PHOHHx blends at various ratios was investigated. Effects of various processing parameters on nanofiber morphology were investigated, such as solution concentration, feeding rate and applied voltage. Crystallinity, chemical structure, and mechanical properties of the electrospun mats were also studied. Graphical Abstract
Persona Perception Scale: Developing and Validating an Instrument for Human-Like Representations of Data

Personas are widely used in software development, system design, and HCI studies. Yet, their evaluation is difficult, and there are no recognized and validated measurement scales to date. To improve this condition, this research develops a persona perception scale based on reviewing relevant literature. We validate the scale through a pilot study with 19 participants, each evaluating three personas (57 evaluations in total). This is the first reported effort to systematically develop and validate an instrument for persona perception measurement. We find the constructs and items of the scale perform well, with factor loadings ranging between 0.60 and 0.95. Reliability, measured as Cronbach's Alpha, is also satisfactory, encouraging us to pursue the use of the scale with a larger sample in future work.
Scalable Linear Algebra on a Relational Database System

As data analytics has become an important application for modern data management systems, a new category of data management system has appeared recently: the scalable linear algebra system. In this paper, we argue that a parallel or distributed database system is actually an excellent platform upon which to build such functionality. Most relational systems already have support for cost-based optimization—which is vital to scaling linear algebra computations—and it is well-known how to make relational systems scale. We show that by making just a few changes to a parallel/ distributed relational database system, such a system can be a competitive platform for scalable linear algebra. Taken together, our results should at least raise the possibility that brand new systems designed from the ground up to support scalable linear algebra are not absolutely necessary, and that such systems could instead be built on top of existing relational technology. Our results also suggest that if scalable linear algebra is to be added to a modern dataflow platform such as Spark, they should be added on top of the system's more structured (relational) data abstractions, rather than being constructed directly on top of the system's raw dataflow operators.
On the bias of finite-view interior tomography using piecewise-constant and non-negativity constraints

It has been widely believed that the non-negativity and the piecewise-constant constraints guarantee a unique solution to an interior tomographic problem. This letter points out that if the number of views is finite, the non-negativity and the piecewise-constant constraints do not guarantee a unique solution to an interior tomographic problem and the reconstruction could be biased by a constant polygon.
Milk Composition for Admixed Dairy Cattle in Tanzania

It is well established that milk composition is affected by the breed and genotype of a cow. The present study investigated the relationship between the proportion of exotic genes and milk composition in Tanzanian crossbred dairy cows. Milk samples were collected from 209 animals kept under smallholder production systems in Rungwe and Lushoto districts of Tanzania. The milk samples were analyzed for the content of components including fat, protein, casein, lactose, solids-not-fat (SNF), and the total solids (TS) through infrared spectroscopy using Milko-Scan FT1 analyzer (Foss Electric, Denmark). Hair samples for DNA analysis were collected from individual cows and breed composition determined using 150,000 single nucleotide polymorphism (SNP) markers. Cows were grouped into four genetic classes based on the proportion of exotic genes present: 25–49, 50–74, 75–84, and >84%, to mimic a backcross to indigenous zebu breed, F1, F2, and F3 crosses, respectively. The breed types were defined based on international commercial dairy breeds as follows: RG (Norwegian Red X Friesian, Norwegian Red X Guernsey, and Norwegian Red X Jersey crosses); RH (Norwegian Red X Holstein crosses); RZ (Norwegian Red X Zebu and Norwegian Red X N’Dama crosses); and ZR (Zebu X GIR, Zebu X Norwegian Red, and Zebu X Holstein crosses). Results obtained indicate low variation in milk composition traits between genetic groups and breed types. For all the milk traits except milk total protein and casein content, no significant differences (p < 0.05) were observed among genetic groups. Protein content was significantly (p < 0.05) higher for genetic group 75–84% at 3.4 ± 0.08% compared to 3.18 ± 0.07% for genetic group >84%. Casein content was significantly lower for genetic group >84% (2.98 ± 0.05%) compared to 3.18 ± 0.09 and 3.16 ± 0.06% for genetic group 25–49 and 75–84%, respectively (p < 0.05). There was no significant difference (p < 0.05) between breed types with respect to milk composition traits. These results suggest that selection of breed types to be used in smallholder systems need not pay much emphasis on milk quality differences as most admixed animals would have similar milk composition profiles. However, a larger sample size would be required to quantify any meaningful differences between groups.
Matching and Merging of Variant Feature Specifications

Model Management addresses the problem of managing an evolving collection of models by capturing the relationships between models and providing well-defined operators to manipulate them. In this paper, we describe two such operators for manipulating feature specifications described using hierarchical state machine models: Match, for finding correspondences between models, and Merge, for combining models with respect to known or hypothesized correspondences between them. Our Match operator is heuristic, making use of both static and behavioral properties of the models to improve the accuracy of matching. Our Merge operator preserves the hierarchical structure of the input models, and handles differences in behavior through parameterization. This enables us to automatically construct merges that preserve the semantics of hierarchical state machines. We report on tool support for our Match and Merge operators, and illustrate and evaluate our work by applying these operators to a set of telecommunication features built by AT&T.
Scanning Micromirror Platform Based on MEMS Technology for Medical Application

This topical review discusses recent development and trends on scanning micromirrors for biomedical applications. This also includes a biomedical micro robot for precise manipulations in a limited volume. The characteristics of medical scanning micromirror are explained in general with the fundamental of microelectromechanical systems (MEMS) for fabrication processes. Along with the explanations of mechanism and design, the principle of actuation are provided for general readers. In this review, several testing methodology and examples are described based on many types of actuators, such as, electrothermal actuators, electrostatic actuators, electromagnetic actuators, pneumatic actuators, and shape memory alloy. Moreover, this review provides description of the key fabrication processes and common materials in order to be a basic guideline for selecting micro-actuators. With recent developments on scanning micromirrors, performances of biomedical application are enhanced for higher resolution, high accuracy, and high dexterity. With further developments on integrations and control schemes, MEMS-based scanning micromirrors would be able to achieve a better performance for medical applications due to small size, ease in microfabrication, mass production, high scanning speed, low power consumption, mechanical stable, and integration compatibility.
Performance Impact Caused by Hidden Bias of Training Data for Recognizing Textual Entailment

The quality of training data is one of the crucial problems when a learning-centered approach is employed. This paper proposes a new method to investigate the quality of a large corpus designed for the recognizing textual entailment (RTE) task. The proposed method, which is inspired by a statistical hypothesis test, consists of two phases: the first phase is to introduce the predictability of textual entailment labels as a null hypothesis which is extremely unacceptable if a target corpus has no hidden bias, and the second phase is to test the null hypothesis using a Naive Bayes model. The experimental result of the Stanford Natural Language Inference (SNLI) corpus does not reject the null hypothesis. Therefore, it indicates that the SNLI corpus has a hidden bias which allows prediction of textual entailment labels from hypothesis sentences even if no context information is given by a premise sentence. This paper also presents the performance impact of NN models for RTE caused by this hidden bias.
A λ-Calculus for Resource Separation

We present a typed λ-calculus for recording resource separation constraints between terms. The calculus contains a novel way of manipulating nested multi-place contexts augmented with constraints, allowing a concise presentation of the typing rules. It is an extension of the affine αλ-calculus. We give a semantics based on sets indexed by resources, and show how the calculus may be extended to handle non-symmetric relations with application to allowable information flow. Finally, we mention some future directions and questions we have about the calculus.