Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive Optics Reveals Photoreceptor Abnormalities in Diabetic Macular Ischemia

Diabetic macular ischemia (DMI) is a phenotype of diabetic retinopathy (DR) associated with chronic hypoxia of retinal tissue. The goal of this prospective observational study was to report evidence of photoreceptor abnormalities using adaptive optics scanning laser ophthalmoscopy (AOSLO) in eyes with DR in the setting of deep capillary plexus (DCP) non-perfusion. Eleven eyes from 11 patients (6 women, age 31–68), diagnosed with DR without macular edema, underwent optical coherence tomography angiography (OCTA) and AOSLO imaging. One patient without OCTA imaging underwent fluorescein angiography to characterize the enlargement of the foveal avascular zone. The parameters studied included photoreceptor heterogeneity packing index (HPi) on AOSLO, as well as DCP non-perfusion and vessel density on OCTA. Using AOSLO, OCTA and spectral domain (SD)-OCT, we observed that photoreceptor abnormalities on AOSLO and SD-OCT were found in eyes with non-perfusion of the DCP on OCTA. All eight eyes with DCP non-flow on OCTA showed photoreceptor abnormalities on AOSLO. Six of the eight eyes also had outer retinal abnormalities on SD-OCT. Three eyes with DR and robust capillary perfusion of the DCP had normal photoreceptors on SD-OCT and AOSLO. Compared to eyes with DR without DCP non-flow, the eight eyes with DCP non-flow had significantly lower HPi (P = 0.013) and parafoveal DCP vessel density (P = 0.016). We found a significant correlation between cone HPi and parafoveal DCP vessel density (r = 0.681, P = 0.030). Using a novel approach with AOSLO and OCTA, this study shows an association between capillary non-perfusion of the DCP and abnormalities in the photoreceptor layer in eyes with DR. This observation is important in confirming the significant contribution of the DCP to oxygen requirements of photoreceptors in DMI, while highlighting the ability of AOSLO to detect subtle photoreceptor changes not always visible on SD-OCT.
Effect of Trilostane and Mitotane on Aldosterone Secretory Reserve in Dogs with Pituitary‐Dependent Hyperadrenocorticism

Background Maximal aldosterone secretion in healthy dogs occurs 30 minutes postadrenocorticotropin (ACTH; 5 μg/kg IV) stimulation. The effect of trilostane and mitotane on aldosterone at that time is unknown. Objectives To assess the effect of trilostane and mitotane in dogs with pituitary‐dependent hyperadrenocorticism on aldosterone secretory reserve. To determine if aldosterone concentration correlates with electrolyte concentrations. Animals Serum collected from 79 client‐owned dogs and 33 stored samples. Methods Client‐owned dogs had ACTH stimulation tests with cortisol concentrations measured at 0 and 60 minutes and aldosterone concentrations measured at 0, 30, and 60 minutes. Stored samples had aldosterone concentrations measured at 0 and 60 minutes. Ten historical clinically healthy controls were included. All had basal sodium and potassium concentrations measured. Results The aldosterone concentrations in the mitotane‐ and trilostane‐treated dogs at 30 and 60 minutes post‐ACTH were significantly lower than in clinically healthy dogs; no significant difference was detected in aldosterone concentration between 30 and 60 minutes in treated dogs. However, a significantly higher percentage of dogs had decreased aldosterone secretory reserve detected at 30 minutes than at 60 minutes. At 30 minutes, decreased secretory reserve was detected in 49% and 78% of trilostane‐ and mitotane‐treated dogs, respectively. No correlation was detected between aldosterone and serum electrolyte concentrations. Conclusions and Clinical Importance Decreased aldosterone secretory reserve is common in trilostane‐ and mitotane‐treated dogs; it cannot be predicted by measurement of serum electrolyte concentrations. Aldosterone concentration at 30 minutes post‐ACTH stimulation identifies more dogs with decreased aldosterone secretory reserve than conventional testing at 60 minutes.
Antidiabetic Effect of Oral Borapetol B Compound, Isolated from the Plant Tinospora crispa, by Stimulating Insulin Release

Aims. To evaluate the antidiabetic properties of borapetol B known as compound 1 (C1) isolated from Tinospora crispa in normoglycemic control Wistar (W) and spontaneously type 2 diabetic Goto-Kakizaki (GK) rats. Methods. The effect of C1 on blood glucose and plasma insulin was assessed by an oral glucose tolerance test. The effect of C1 on insulin secretion was assessed by batch incubation and perifusion experiments using isolated pancreatic islets. Results. An acute oral administration of C1 improved blood glucose levels in treated versus placebo groups with areas under glucose curves 0–120 min being 72 ± 17 versus 344 ± 10 mmol/L (P < 0.001) and 492 ± 63 versus 862 ± 55 mmol/L (P < 0.01) in W and GK rats, respectively. Plasma insulin levels were increased by 2-fold in treated W and GK rats versus placebo group at 30 min (P < 0.05). C1 dose-dependently increased insulin secretion from W and GK isolated islets at 3.3 mM and 16.7 mM glucose. The perifusions of isolated islets indicated that C1 did not cause leakage of insulin by damaging islet beta cells (P < 0.001). Conclusion. This study provides evidence that borapetol B (C1) has antidiabetic properties mainly due to its stimulation of insulin release.
Modulo 2^n+1 Arithmetic Units with Embedded Diminished-to-Normal Conversion

The diminished-one representation has been proposed for RNS-based systems with moduli of the 2^n+1 forms as an encoding that is more efficient than the normal representation in the arithmetic processing units. However, its use necessitates a two-step reverse conversion, in which a diminished-to-normal conversion is first performed before the final residue-to-binary conversion resulting in performance loss. In this paper we introduce efficient modulo 2^n+1 adders, sub tractors and multipliers that accept diminished-one operands at their inputs and derive normal operands at their outputs, that is, we embed the diminished-to-normal conversion within the arithmetic processing. Experimental results show that the proposed one-step approach is more efficient in terms of delay.
Therapeutic Potential of Human Adipose-Derived Stem Cells (ADSCs) from Cancer Patients: A Pilot Study

Mesenchymal stem cells from adipose tissue (ADSCs) are an important source of cells for regenerative medicine. The therapeutic effect of culture-expanded adipose derived stem cells has been shown; however, optimal xeno-free culture conditions remain to be determined. Cancer patients, specifically those undergoing invasive surgery, constitute a subgroup of patients who could benefit from autologous stem cell transplantation. Although regenerative potential of their ADSCs could be affected by the disease and/or treatment, we are not aware of any study that has evaluated the therapeutic potential of ADSCs isolated from cancer patients in reference to that of ADSCs derived from healthy subjects. Here we report that ADSCs isolated from subabdominal adipose tissue of patients with urological neoplasms yielded similar growth kinetics, presented equivalent mesenchymal surface markers and showed similar differentiation potential into distinct mesodermal cell lineages: adipocytes, chondroblasts and osteoblasts than ADSCs isolated from adipose tissue of age-matched non-oncogenic participants, all under xeno-free growth culture conditions. Molecular karyotyping of patient expanded ADSCs genomes showed no disease-related alterations indicating their safety. In addition, vesicles <100 nm identified as exosomes (EXOs) which may be at least partly responsible for the attributed therapeutic paracrine effects of the ADSCs were effectively isolated from ADSCs and showed equivalent miRNA content regardless they were derived from cancer patients or non-oncogenic participants indicating that the repair capabilities of xeno-free expanded ADSCs are not compromised by patient condition and therefore their xeno-free culture expanded ADSCs should be suitable for autologous stem cell transplantation in a clinical setting.
Treatments for Biomedical Abnormalities Associated with Autism Spectrum Disorder

Recent studies point to the effectiveness of novel treatments that address physiological abnormalities associated with autism spectrum disorder (ASD). This is significant because safe and effective treatments for ASD remain limited. These physiological abnormalities as well as studies addressing treatments of these abnormalities are reviewed in this article. Treatments commonly used to treat mitochondrial disease have been found to improve both core and associated ASD symptoms. Double-blind, placebo-controlled (DBPC) studies have investigated l-carnitine and a multivitamin containing B vitamins, antioxidants, vitamin E, and co-enzyme Q10 while non-blinded studies have investigated ubiquinol. Controlled and uncontrolled studies using folinic acid, a reduced form of folate, have reported marked improvements in core and associated ASD symptoms in some children with ASD and folate related pathway abnormities. Treatments that could address redox metabolism abnormalities include methylcobalamin with and without folinic acid in open-label studies and vitamin C and N-acetyl-l-cysteine in DBPC studies. These studies have reported improved core and associated ASD symptoms with these treatments. Lastly, both open-label and DBPC studies have reported improvements in core and associated ASD symptoms with tetrahydrobiopterin. Overall, these treatments were generally well-tolerated without significant adverse effects for most children, although we review the reported adverse effects in detail. This review provides evidence for potentially safe and effective treatments for core and associated symptoms of ASD that target underlying known physiological abnormalities associated with ASD. Further research is needed to define subgroups of children with ASD in which these treatments may be most effective as well as confirm their efficacy in DBPC, large-scale multicenter studies.
Nonstationary stochastic analysis of steady state flow through variably saturated, heterogeneous media

In this study we develop a first‐order, nonstationary stochastic model for steady state, unsaturated flow in randomly heterogeneous media. The model is applicable to the entire domain of a bounded vadose zone, unlike most of the existing stochastic models. Because of its nonstationarity, we solve it by the numerical technique of finite differences, which renders the flexibility in handling different boundary conditions, input covariance structures, and soil constitutive relationships. We illustrate the model results in one and two dimensions for soils described by the Brooks‐Corey constitutive model. It is found that the flow quantities such as suction head, effective water content, unsaturated hydraulic conductivity, and velocity are nonstationary near the water table and approach stationarity as the vertical distance from the water table increases. The stationary limits and the critical vertical distance at which stationarity is attained depend on soil types and recharge rates. The smaller the recharge rate is, the larger the critical distance; and the coarser the soil texture is, the smaller the distance. One important implication of this is that the existing simpler, gravity‐dominated flow models may provide good approximations for flow in vadose zones of large thickness and/or coarse‐textured soils although they may not be valid for vadose zones of fine‐textured soils with a shallow water table. It is also found that the vertical extent of a domain where nonstationarity is important may be estimated by solving the one‐dimensional Richards equation for mean head with average soil properties and appropriate boundary conditions. On the basis of the mean head, one may then determine whether the full, nonstationary model must be solved or whether a simpler, gavity‐dominated model will suffice. The flow quantities are also nonstationary in the horizontal direction near the lateral boundaries, as found for flow in saturated zones.
Mastering the Transition to Product-Service Provision: Insights into Business Models, Learning Activities, and Capabilities

OVERVIEW: Traditional manufacturing companies are increasingly offering industrial services in order to secure their position in the globally competitive environment. However, little is known about the extent and effect of this transition. Based on a large-scale survey of Finnish manufacturing companies, this study offers descriptive statistics for current industrial service offerings. Merely adding on simple services to a current product offering is shown to be negatively associated with financial performance. Rather, our statistical analysis suggests a thorough and comprehensive organizational transformation is required to generate significant financial value. In addition, qualitative data from globally recognized Swedish and Finnish frontrunner manufacturing companies offer insights into how these market leaders have successfully navigated the organizational challenges of such a transformation to offer successful industrial product-service systems. Based on the data, we outline four distinctive capabilities and associated key learning activities required to facilitate a successful transition toward becoming a high-value industrial product-service provider.
Neural network model-based training algorithm for transient signal analysis

The quality of electricity supply has become a major concern of electric utilities in power system. In order to acquire the improved power quality, it is required to know the sources of power quality disturbances and find ways to mitigate them. This paper presents a new approach to detect and classify power quality disturbances based on wavelet transformation and neural network. By means of wavelet analysis, the properties of time-frequency domain demonstrate that the complex wavelet transformation is an excellent tool for processing the transient signal of power system disturbances. The feature extraction of disturbance is explored to obtain dynamic parameters, in which the combined information can be obtained from both magnitude and argument coefficients to extract the desired band of the transient signal and detect the disturbance source. The improved training algorithm is utilized to complete the neural network parameters initialization, acquiring good convergence. The simulation results and analysis demonstrate that the proposed method is effective for transient signal feature extraction.
Regulation of androgen receptor splice variant AR3 by PCGEM1

The androgen receptor (AR) is required for prostate development and is also a major driver of prostate cancer pathogenesis. Thus androgen deprivation therapy (ADT) is the mainstay of treatment for advanced prostate cancer. However, castration resistance due to expression of constitutively active AR splice variants is a significant challenge to prostate cancer therapy; little is known why effectiveness of ADT can only last for a relatively short time. In the present study, we show that PCGEM1 interacts with splicing factors heterogeneous nuclear ribonucleoprotein (hnRNP) A1 and U2AF65, as determined by RNA precipitation and Western blot, suggesting a role for PCGEM1 in alternative splicing. In support of this possibility, PCGEM1 is correlated with AR3, a predominant and clinically important form of AR splice variants in prostate cancer. Moreover, androgen deprivation (AD) induces PCGEM1 and causes its accumulation in nuclear speckles. Finally, we show that the AD-induced PCGEM1 regulates the competition between hnRNP A1 and U2AF65 for AR pre-mRNA. AD promotes PCGEM1 to interact with both hnRNP A1 and U2AF65 with different consequences. While the interaction of PCGEM1 with hnRNP A1 suppresses AR3 by exon skipping, its interaction with U2AF65 promotes AR3 by exonization. Together, we demonstrate an AD-mediated AR3 expression involving PCGEM1 and splicing factors.
Procedure-based development platform for communication protocol stack software

This paper presents a novel approach for developing a communication protocol stack efficiently. In this approach, a communication protocol stack is implemented directly from the message sequence chart (MSC) describing its behavior. To verify the proposed approach, we implemented a procedure-based development platform composed of MSC design tool, protocol stack framework, test framework, and MSC extractor. Procedures and their dependencies are specified through the MSC design tool during the design phase. They are translated into data structures and template codes which the protocol stack framework can handle during the implementation phase. These are further reused in the test framework with test configuration at the test phase. The test framework also supports reproduction tests with extracted MSCs from the test logs. This approach enables users to examine the system behavior by comparing MSCs — one drawn during the design phase and the other collected under the test phase, which makes it easier for the users to revise the design based on the test result. Finally, a virtuous development cycle is accomplished for the development process of protocol stack from the design to the test. We show that our platform is superior to FSM-based framework in terms of traceability, maintainability, and productivity by implementing LTE RRC protocol using both frameworks.
Phonon heat conduction in a semiconductor nanowire

A model for phonon heat conduction in a semiconductor nanowire with dimensions comparable to the phonon mean free path is developed. It is based on the solution of Boltzmann’s equation, which takes into account (i) modification of the acoustic phonon dispersion due to spatial confinement, and (ii) change in the nonequilibrium phonon distribution due to partially diffuse boundary scattering. Numerical simulation is performed for a silicon nanowire with boundaries characterized by different interface roughness. Phonon confinement and boundary scattering lead to a significant decrease of the lattice thermal conductivity. The value of this decrease and its interface roughness and temperature dependence are different from the predictions of the early models. The observed change in thermal resistance has to be taken into account in simulation of deep-submicron and nanometer-scale devices.
GPU-Accelerated Query by Humming Using Modified SPRING Algorithm

Current query by humming system can hardly be extended to large massive database as most of them adopt the features extracted from MIDI files which are not widely used and the very time-consuming match methods. In this work, we regard query by humming as a subsequence similarity match problem and exploit the modified SPRING algorithm instead of DTW as the core match method to compare the melody feature extracted from polyphonic music. The SPRING algorithm reduces the algorithm complexity of subsequence match dramatically. Furthermore, we also make it possible for our system to achieve a high speedup over the serial version on different GPU platforms. Experimental results show that our system has more advantages over the state of the art subsequence match method, and has a good scalability to massive database. The processing capacity can reach to thousands of sequences match per second under down sampling. At the same time, the retrieval accuracy results related to all aspects of query by humming point out the encountered problems and the future direction.
Villains, architects and micro-managers: what tabula rasa teaches us about game orchestration

Players of digital games are limited by the constraints of the game's implementation. Players cannot fly a kite, plant a tree or make friends with a dragon if these activities were not coded within the game. Game orchestration relaxes these restrictions by allowing players to create game narratives and settings as the game is being played. This enables players to express their creativity beyond the strictures of the game's implementation. We present Tabula Rasa, a novel game orchestration tool based on an efficient tabletop interface. Based on a study of 20 game orchestration sessions using Tabula Rasa, we identify five behavioural patterns adopted by orchestrators, and four styles of collaborative interaction between orchestrators and players. Finally, we present recommendations for designers of game orchestration systems.
Low Rank ADI Solution of Sylvester Equation via Exact Shifts

The solution to a general Sylvester equation AX−XB = GF ∗ with a low rank righthand side is analyzed quantitatively through Low-rank Alternating-DirectionalImplicit method (LR-ADI) with exact shifts. New bounds and perturbation bounds on X are obtained. A distinguished feature of these bounds is that they reflect the interplay between the eigenvalue decompositions of A and B and the right-hand side factors G and F . Numerical examples suggest that because of this inclusion of details, new perturbation bounds are much sharper than the existing ones.
An efficient genetic algorithm approach for solving routing and spectrum assignment problem

In flex-grid optical network, routing and spectrum assignment (RSA) problem is a crucial task for planning and operating. Due to the non-deterministic polynomial time (NP-hard) complexity of problem, efficient computing techniques are always sought out with the aim to not only achieve good solutions but also in an efficient time span. In this context, this paper addresses the static version of RSA problem in a single objective scenario. We propose efficient meta-heuristic based on genetic algorithm (GA) to provide (near-) optimal solutions to the problem. The effectiveness of GA-based heuristic is bench-marked with exact approach based on integer linear programming (ILP) and other traditional heuristics for a set of scenarios. It is shown that the proposed GA heuristic exhibits better performance than typical heuristics and indeed could achieve optimal solutions in most cases while the running time is still highly manageable.
Fluctuating asymmetry and preferences for sex-typical bodily characteristics

Body size and shape seem to have been sexually selected in a variety of species, including humans, but little is known about what attractive bodies signal about underlying genotypic or phenotypic quality. A widely used indicator of phenotypic quality in evolutionary analyses is degree of symmetry (i.e., fluctuating asymmetry, FA) because it is a marker of developmental stability, which is defined as an organism's ability to develop toward an adaptive end-point despite perturbations during its ontogeny. Here we sought to establish whether attractive bodies signal low FA to observers, and, if so, which aspects of attractive bodies are most predictive of lower FA. We used a 3D optical body scanner to measure FA and to isolate size and shape characteristics in a sample of 77 individuals (40 males and 37 females). From the 3D body scan data, 360° videos were created that separated body shape from other aspects of visual appearance (e.g., skin color and facial features). These videos then were presented to 87 evaluators for attractiveness ratings. We found strong negative correlations between FA and bodily attractiveness in both sexes. Further, sex-typical body size and shape characteristics were rated as attractive and correlated negatively with FA. Finally, geometric morphometric analysis of joint configurations revealed that sex-typical joint configurations were associated with both perceived attractiveness and lower FA for male but not for female bodies. In sum, body size and shape seem to show evidence of sexual selection and indicate important information about the phenotypic quality of individuals.