Miracle-dz/UniFAR-FTUs huggingface dataset:
Ignoring variation in wood density drives substantial bias in biomass estimates across spatial scales

Rapid development of remote sensing and Light Detection and Ranging (LiDAR) technology has refined estimates of tree architecture and extrapolation of biomass across large spatial scales. Yet, current biomass maps show significant discrepancies and mismatch to independent ground data. A potential obstacle to accurate biomass estimation is the loss of information on wood density, which can vary at local and regional scales, in the extrapolation process. Here we investigate if variation in wood specific gravity (WSG) substantially impacts the distribution of above-ground biomass (AGB) across a range of scales from local plots to large regions. We collected wood cores and measured tree volume in 341 forest sites across large altitudinal and climatic gradients in Colombia. At all spatial scales, variation in WSG was substantial compared to variation in volume. Imputing study-wide average values of WSG induced regional biases in AGB estimates of almost 30%, consequently undervaluing the difference between forest areas of low and high average wood density. Further, neither stem size nor climate usefully predicted WSG when accounting for spatial dependencies among our sampling plots. These results suggest that remote sensing- and LiDAR-based projections to biomass estimates can be considerably improved by explicitly accounting for spatial variation in WSG, necessitating further research on the spatial distribution of WSG and potential environmental predictors to advance efficient and accurate large-scale mapping of biomass.
The 3D-Printed Low-Cost Delta Robot Óscar: Technology Overview and Benchmarking

: Robotics is undoubtedly one of the most inﬂuential ﬁelds of modern technology in changing the very nature of our society. Parallel Delta robots have for a long time been mainly focused on a niche market but compared to serial anthropomorphic robots they present several simplicity and improved dynamics features. Additive manufacturing (AM) and 3D-printing technologies are enabling rapid changes in robotic engineering as we classically know it, allowing for greater creativity and freedom in mechatronics design and innovation. The effective beneﬁts of far-reaching design freedom in terms of geometry, materials, and manufacturing accessibility, are now starting to become apparent, answering many complex technical questions and scientiﬁc uncertainties that go beyond basic design and functional knowledge and that require engineering skills and scientiﬁc analysis. The Delta robot, as one of the most signiﬁcant industrialized parallel robots due to its simplicity, is considered in this work, which provides an overview of the multidisciplinary aspects of the new Smile.Tech’s 3D-printed and low-cost Delta robot Oscar family. It contains a concise analysis of the current state of the art and use of Delta robots, as well as discussion of the Delta architecture, interface software, and virtual operation environments. The article concludes with a market analysis, a summary of the major manufacturers and currently available Delta models, and a benchmarking study of their major operating and technical features.
A Multistep DNA-Based Methodology for Accurate Authentication of Sturgeon Species

The sturgeons (order Acipenseriformes) are caviar producers and some of the most valuable fish species worldwide. Due to different reasons, wild populations are now at the brink of extinction. The high demand for caviar has led to the development of aquaculture for restocking and caviar production. Since the caviar from different species has different prices depending on the quality and attempts of commercial fraud based on species substitution have been found, correct species identification is more than necessary. We report a new multistep methodology for an accurate species identification based on both nuclear and mitochondrial markers. Our test integrates data from the analysis of microsatellites (Afu19, Afu34, Afu39, Afu54, Aox27, AoxD234, AnacC11 and AnacE4), nuclear gene markers (RPS7, vimentin and rhodopsin) and mtDNA barcoding to give a reliable molecular diagnostic for five sturgeon species (Huso huso, Acipenser stellatus, Acipenser ruthenus, Acipenser gueldenstaedtii and Acipenser baerii). In addition to species identification, our methodology allows the identification of bester, sterbe and best beluga hybrids, but also the identification of hybrids of unknown origin. This methodology has a good potential to contribute to the conservation of highly threatened sturgeon populations and also to the traceability of their products.
Effect of the casein to fat ratio on the functional properties of Prato cheese

This study aimed to evaluate the effect of casein to fat ratios (0.68, 0.72, and 0.76) on the functional properties of Prato cheese at 2, 15, 30, and 45 days of ripening. The different ratios did not interfere with the physicochemical characteristics, pH, Aw, proteolysis indices, color parameters, sliceability and sensory profile of the cheeses among the treatments. However, pH, proteolysis indices, texture profile, L* and b* color parameters of the cheeses changed through the ripening time. The cheeses made from milk standardized to casein/fat ratio of 0.68 presented lower chewiness values. The casein to fat ratio of 0.68 increased the protein and fat recoveries, and provided greater meltability and greater formation of free oil when compared to cheeses made from milk with casein to fat ratio of 0.76. Therefore, casein to fat ratio of 0.72 is recommended for the production of Prato cheese as the cheese presents good functional properties at this value, such as intermediate melting and chewiness, and less release of free oil.
Numerical Method for Capacitance Matrix of Coaxial Cables of Finite Length

We put forward a moment-method-based procedure to determine the capacitance matrix of coaxial finite-long cables with. In this procedure,the cables are represented by a number of charged cylindrical surfaces among which dielectric material is filled. The external surface is covered with insulated sheath. Then each cable is divided into a set of cylindrical elements along the cable axis. Average potential and electric field equations are then established respectively to build a matrix equation. Through matrix calculation,the capacitance matrix of the cables can be obtained. For typical cable installation,the numerical results for the capacitance matrix are presented. By comparing with a two-dimensional numerical method,the procedure presented is validated finally.
An Application of Support Vector Machine in Foundation Settlement Prediction

The support vector machine(SVM) forecasting method is introduced into foundation settlement forecasting.SVM is a new machine learning method based on the statistical learning theory.SVM for predicting foundation settlement is analyzed.The method of support vector machines is proposed for building predicting model.Based on a set of samples,practical effectiveness of the theory of support vector machines for predicting foundation settlement is discussed.The results indicate that it is effective and feasible to use this method and the nonlinear mapping relation between foundation settlement and its influence factor can be expressed well.It will provide a new method to predict foundation settlement.
Capturing Subtle Neurocognitive Differences in Children with and without Tourette Syndrome through a Fine-Grained Analysis of Design Fluency Profiles

Background: Tourette syndrome (TS) can be accompanied by neurocognitive impairment. Only a few studies have focused on executive function assessment in TS using design fluency, providing preliminary results. This study aimed to characterize the detailed design fluency profile of children with TS compared with neurotypical children, while addressing the central concern of frequent comorbidities in studies on TS by considering tic severity and attention-deficit/hyperactivity disorder (ADHD) symptoms and diagnosis. Methods: Sixty-one children aged between 6 and 15 years participated and were divided into a TS group (n = 28 (with ADHD n = 15)) and a control group (n = 33). Our objective was addressed by examining a wide range of measures of the Five-Point-Test, presumably sensitive to frontostriatal dysfunction. The total number of designs, repetitions, repetition ratio, unique designs, and numerical, spatial, and total strategies were examined for the total duration of the test (global measures) and at five equal time intervals (process measures). Results: The TS group produced significantly fewer numerical strategies. Groups did not differ in other global or process measures. ADHD did not affect performance. Conclusions: Children with TS do not inherently show general executive dysfunction but may present with subtle neurocognitive characteristics here revealed by comprehensive design fluency profiles.
Feasibility of Patient Navigation-Based Smoking Cessation Program in Cancer Patients

Continued smoking after a cancer diagnosis is causally associated with increased risks of all-cause and cancer-specific mortality, and of smoking-related second primary cancers. Patient navigation provides individualized assistance to address barriers to smoking cessation treatment and represents a promising bridge to smoking cessation in persons with cancer who smoke cigarettes. We conducted a single-arm interventional cohort study of current smokers identified through prospective health record screening and recruited from Penn State Cancer Institute outpatient clinics. Consented participants received two telephone intervention sessions and gain-framed messaging-based smoking cessation educational materials designed for persons with cancer. The primary study outcome was the feasibility of the patient navigation-based intervention; the secondary outcome was the engagement in smoking cessation treatment at the two-month follow-up. Of 1168 unique screened Cancer Institute patients, 134 (11.5%) were identified as current cigarette smokers. Among 67 patients approached at outpatient clinics, 24 (35.8%) were interested in participating, 12 (17.9%) were enrolled, eight (11.9%) completed the intervention sessions and study assessments, and six engaged in smoking cessation treatment. The participants expressed satisfaction with the intervention sessions (median = 8.5, scale 0–10). The low recruitment rates preclude patient navigation as a feasible method for connecting cancer patients to smoking cessation treatment resources.
Knowledge management for SMEs: a pragmatic approach

ABSTRACT Active participation of Small and Medium Enterprises (SMEs) in the digital revolution is jeopardised due to low technology adoption and inept management of skills and innovation resources. Apparently, firms that contrive firm knowledge proficiently qualify to address the demands of a new environment. As SMEs contend with their know-how, it becomes essential to practice Knowledge Management (KM). However, to avoid implementation failure and ease prioritisation of resources, being aware of Critical Success Factors (CSFs) of KM is vital. As research on CSFs of KM in SMEs has been inherently insufficient and inconsistent with literature on Critical Failure Factors (CFFs) of KM, there was a need to revise discussion on and propose an enhanced set of four CSFs of KM for SMEs by adopting the “Theory Adaptation” research design by amalgamating CSFs and CFFs of KM. Later, a discussion on KM planning followed to facilitate application of the proposed CSFs.
In Vitro Hydrolytic Degradation of Polyester-Based Scaffolds under Static and Dynamic Conditions in a Customized Perfusion Bioreactor

Creating biofunctional artificial scaffolds could potentially meet the demand of patients suffering from bone defects without having to rely on donors or autologous transplantation. Three-dimensional (3D) printing has emerged as a promising tool to fabricate, by computer design, biodegradable polymeric scaffolds with high precision and accuracy, using patient-specific anatomical data. Achieving controlled degradation profiles of 3D printed polymeric scaffolds is an essential feature to consider to match them with the tissue regeneration rate. Thus, achieving a thorough characterization of the biomaterial degradation kinetics in physiological conditions is needed. Here, 50:50 blends made of poly(ε-caprolactone)–Poly(D,L-lactic-co-glycolic acid (PCL-PLGA) were used to fabricate cylindrical scaffolds by 3D printing (⌀ 7 × 2 mm). Their hydrolytic degradation under static and dynamic conditions was characterized and quantified. For this purpose, we designed and in-house fabricated a customized bioreactor. Several techniques were used to characterize the degradation of the parent polymers: X-ray Photoelectron Spectroscopy (XPS), Gel Permeation Chromatography (GPC), Scanning Electron Microscopy (SEM), evaluation of the mechanical properties, weigh loss measurements as well as the monitoring of the degradation media pH. Our results showed that flow perfusion is critical in the degradation process of PCL-PLGA based scaffolds implying an accelerated hydrolysis compared to the ones studied under static conditions, and up to 4 weeks are needed to observe significant degradation in polyester scaffolds of this size and chemical composition. Our degradation study and characterization methodology are relevant for an accurate design and to tailor the physicochemical properties of polyester-based scaffolds for bone tissue engineering.
Prostate Cancer and Sleep Disorders: A Systematic Review

Simple Summary Longer survival times for prostate cancer patients due to efficient treatments consisting of local radiotherapy, prostatectomy and androgen-deprivation therapy, as well as androgen-receptor-targeted agents, increases the importance of side effect management. Sleep disturbances are higher in this group than the general population and no clear mechanism(s) explains this. This systematic review finds a reported effect in 14 of 16 included studies on sleep quality changes for these patients. All reported treatments showed some kind of negative effect on sleep quality, including ADT. Limitations are discussed and recommendations made for progressing the understanding and then for mitigation strategies of these side effects. Abstract Prostate cancer (PCa) treatment involves multiple strategies depending on the disease’s stage. Androgen deprivation therapy (ADT) remains the gold standard for advanced and metastatic stages. Sleep quality has been suggested as being additionally influenced also by local radiotherapy, prostatectomy and androgen-receptor (AR)-targeted agents. We performed a systematic review exploring the landscape of studies published between 1 January 1990 and 31 July 2021, investigating sleep disturbances in PCa patients receiving active treatments, including the influence of hormonal therapy on sleep quality as a factor affecting their quality of life. Out of 45 articles identified, 16 studies were selected, which recruited patients with PCa, undergoing active treatment in either a prospective longitudinal or cross-sectional study. Development of sleep disorders or changes in sleep quality were reported in 14 out of 16 trials included. Only five trials included objective measurements such as actigraphy, mostly at one time point and without a baseline assessment. Limitations to be addressed are the small number of existing trials, lack of randomized trials and heterogeneity of methodologies used. This systematic review outlines the lack of prospective trials investigating sleep disorders, with a rigorous methodology, in homogeneous cohorts of PCa patients. Future trials are needed to clarify the prevalence and impact of this side effect of PCa treatments.
Real-time flexible endoscope navigation within bladder phantom having sparse non-distinct features is enhanced with robotic control

Endoscopic inspection of the bladder is called cystoscopy, and over 1 million are performed annually in the USA.1 Robotic assistance of the procedure is being considered to overcome healthcare disparities due to geographic distances. To ensure safety, real-time navigation by simultaneous localization and mapping (SLAM) of the cystoscope in the bladder is desired. However, the near-featureless bladder wall and irregular movement of the monocular cystoscope by manual operation has made SLAM-based navigation a difficult challenge. In this work we develop a robot-assisted approach in a bladder phantom using a commercial flexible cystoscope. With this simple remote-controlled robot, we have succeeded in creating a series of real-time 2.5D reconstructions of the bladder interior wall. In post-processing, we combine those 2.5D results and achieve a 3D reconstruction. We compared SLAM performance using the robot and manual control under different scanning speeds. In comparison to manual control using the same cystoscope at 1x, 2x and 3x speeds, the robotic-assistance provides significantly more robust and accurate reconstructions of the camera trajectories and bladder wall locations in real-time.
Increasing of Blood Brain Barrier Permeability and the Association With Depression and Anxiety in Systemic Lupus Erythematosus Patients

Objective To study changes in blood brain barrier (BBB) permeability in systemic lupus erythematosus (SLE) patients, and explore the association between the alterations in BBB permeability and depression/anxiety in SLE. Methods Brain dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) images were collected from 42 SLE patients and 23 healthy controls (HCs). Based on the Patlak pharmacokinetic model, the Ktrans value of each voxel in the whole brain of each subject was calculated. BBB permeability indicator (the Ktrans value) between SLE patients and healthy control group was compared. Hamilton Depression Scale (HAMD) and Hamilton Anxiety Scale (HAMA) were used to assess the mental health of SLE patients. The difference in BBB permeability was compared on SLE patients with depression/anxiety, SLE patients without depression/anxiety and HCs by ANOVA analysis. Results The Ktrans value of the right insular region of the SLE group was significantly higher than that of the healthy control group. And the Ktrans value of the right insular region in SLE patients with depression/anxiety was significantly increased compared with SLE patients without depression/anxiety and HCs. Conclusions SLE patients have increased BBB permeability, mainly in the right insular area. The increased BBB permeability in the right insular region is associated with the depression/anxiety in SLE patients.
A Study on Compressive Sensing based Clustering algorithms in Wireless Sensor Networks for reduced data transmissions

Energy Efficiency plays a vital role in Wireless Sensor Networks (WSN) because of the limited battery power of nodes. Data Aggregation techniques help in reducing the redundant data transmissions which results in reduced energy consumption. Compressive Sensing (CS) is one of the effective signal processing techniques which helps in reducing the number of transmissions resulting in improved energy efficiency. Clustering is also a proven method of energy efficient data transmission. Employing the CS technique in cluster based WSN gains advantages of both and the outcome of which is further reduction in energy consumption. In this paper, a review of algorithms which employ CS in cluster based WSN is made and explanation of the same is given in brief. Some algorithms employ plain-CS and some employ hybrid-CS techniques. Using the sparse representation of the data vector in some orthonormal basis, even with smaller number of measurements, the data can be reconstructed accurately. First, we have given the details of compressive sensing and the possible sparse transforms, measurement matrices and data reconstruction algorithms. Then, recent works which exploit CS in clustering algorithms are discussed and comparison of the same is provided.
Accurate measurement of thin film mechanical properties using nanoindentation

For decades, nanoindentation has been used for measuring mechanical properties of films with the widely used assumption that if the indentation depth does not exceed 10% of the film thickness, the substrate influence is negligible. The 10% rule was originally deduced for much thicker metallic films on steel substrates and involved only the hardness measurement. Thus, the boundaries of usability for measuring thin film elastic modulus may differ. Two known material systems of Mo and MoTa thin films on Si substrates are examined with nanoindentation and numerical modeling to show the limitations in measuring elastic moduli. An assessment of the hardness and elastic modulus as a function of contact depth and accurate modeling of the film/substrate deformation confirms the 10% rule for hardness measurements. For elastic modulus, the indentation depths should be much smaller. Results provide a recommended testing protocol for accurate assessment of thin film elastic modulus using nanoindentation.
Effect of Distributing Steel Fibers on Some Properties of Slurry Infiltrated Fiber Concrete

The slurry infiltrated fiber concrete (SIFCON) is nowadays considered a special type of high fiber content concrete; it is high strength and high performance material. This paper investigates the effect of spread steel fiber into the slurry mortar on some properties of SIFCON. According to fiber distribution, two sets were used in this investigation. The first set consisted of randomly distributing fibers inside the slurry. The second set was by placing the fibers in an orderly manner inside the slurry. Crimped steel fibers with an aspect ratio of (60) were used. Two different volume fractions percentage of (7% and 9%) by volume of mold were used in both sets for this study. Also, a w/c ratio of (0.35) and superplasticizer of (1%) by weight of cement was used to ensure the penetration of the slurry inside the fibers. The compressive and flexural strength were conducted on standard cubes (10*10*10) cm and prisms of (40*7*7) cm respectively to find the effect of how the steel fibers were distributed. The results showed that distributing the fibers randomly gave better results than the ordered distribution. The increment percentage in compressive strength and flexural strength were (1.5%, 6.9%, 23%, and 6.5%), respectively, for both sets and both fiber volume fractions (7% and 9%).
A Unified Framework for Bidirectional Prototype Learning From Contaminated Faces Across Heterogeneous Domains

Existing heterogeneous face synthesis (HFS) methods focus on performing accurate image-to-image translation across domains, while they cannot effectively remove the nuisance facial variations such as poses, expressions or occlusions. To address such challenges, this paper studies a new practical heterogeneous prototype learning (HPL) problem. To be specific, given a face image contaminated by facial variations from a source domain, HPL aims to reconstruct the variation-free prototype in a specified target domain. To tackle HPL, we propose a unified and end-to-end framework named bidirectional heterogeneous prototype learning (BHPL). As a bidirectional learning framework, BHPL is able to simultaneously reconstruct the heterogeneous prototypes across source-to-target as well as target-to-source domains. Furthermore, BHPL is capable of learning the identity prototype features for the contaminated face images from both source and target domains in order to perform robust heterogeneous face recognition. BHPL consists of an encoder-decoder structural generator and two dual-task discriminators, which play an adversarial game such that the generator learns the identity prototype feature and generates the cross-domain identity-preserved prototype for each input face image from both domains, and the discriminators accurately predict face identity and distinguish real versus fake prototypes. Empirically studies on multiple heterogeneous face datasets containing facial variations demonstrate the effectiveness of BHPL.