Miracle-dz/UniFAR-FTUs huggingface dataset:
Preparation of Particleboard Using Dialdehyde Starch and Corn Stalk

Particleboard was manufactured using dialdehyde starch (DAS) as the adhesive and corn stalk as the matrix. The adhesive was prepared via the oxidation of tapioca starch in sodium periodate. The DAS was characterized by Fourier transform infrared (FTIR) spectroscopy. The effect of the hot pressing temperature, board density, and DAS dosage on the physical properties of particleboard was studied. The cross-section morphology of particleboard was observed via scanning electron microscopy (SEM). The absorption peak of the aldehyde group appeared at 1731 cm-1 after the tapioca starch was oxidized by sodium periodate, indicating that DAS had formed. Both the modulus of rupture (MOR) and modulus of elasticity (MOE) increased first and then decreased, with the increase of hot pressing temperature, board density, and DAS dosage. Within a certain range, the increase of hot pressing temperature, board density, and DAS dosage reduced the thickness swelling (TS) and improved the particleboard water resistance. During the particleboard hot pressing process, DAS filled the spaces of the corn stalk and acted as an adhesive to bind the corn stalks tightly together, thereby improving the physical, mechanical, and water resistance properties of the particleboard.
Iron Oxides as Geochemical Nanovectors for Metal Transport in Soil-River Systems

Topsoils are often contaminated by trace metals, and it is important to understand how different processes govern the transport of such metals to fresh and marine waters. This paper presents measurements of natural nanoparticles and colloidal organic matter in soil and river samples from Germany and Sweden. In our analytical approach, a nanoparticle separation technique is combined with multielement detection and applied to soil and river samples to link the macroscale field observations with detailed molecular studies in the laboratory. It was determined that lead is associated with iron oxide colloids, which are ubiquitous nanoparticles that can be efficiently transported. Eventually both iron oxides and lead are removed by flocculation under conditions of estuarine mixing. Iron-rich nanoparticles compete efficiently with natural organic matter (NOM) complexation for lead binding in both the soil and river systems studied.
Efficient Deep Learning Network With Multi-Streams for Android Malware Family Classification

It is important to effectively detect, mitigate, and defend against Android malware attacks, because Android malware has long represented a major threat to Android app security. Characterizing and classifying similar malicious apps into groups plays a particularly crucial role in building a secure Android app ecosystem. The classification of malware families can efficiently enhance the malware detection process and systematically elucidate malware patterns. In this paper, we propose a novel efficient deep learning network with multi-streams for Android malware family classification. We first obtain the input data for a convolutional neural network (CNN) in string format from some main files or sections contained in each Android malicious app. We then classify malware families by applying a 1-dimensional convolution filter-based network for the files or sections. Further, by using gradient analysis to visualize the important files and sections in malicious apps, we attempt to intuitively grasp which files or sections are the most significant for malware family classification. To validate the effectiveness of our approach, we conduct extensive experiments with the well-known DREBIN and AMD malware datasets, and we compare our approach with existing methods. Our experimental results show that the 1D CNN model is more accurate than the 2D CNN model, and that the code_item part in the classes.dex is the most relevant feature for malware classification, as it is more relevant than other parts such as AndroidManifest.xml and certificate. The proposed method achieves the best accuracy of 93.2% by using 1D convolution filters with multi-streams for the main files and sections of the malware samples.
Production and Evaluation of Yoghurt from Mixtures of Cow Milk , Milk Extract from Soybean and Tiger Nut

The proportions of cow milk, milk extracts from soybean and tiger nut were varied resulting in producing eight formulations. Yoghourt was produced from eight formulations and their physicochemical properties, sensory evaluation and microbial counts were determined. The fat, protein, ash and carbohydrate contents of yoghourt ranged from 1.15 – 3.26%, 2. 14 – 3.56%, 0.22 – 0.68% and 3.77 – 9.27%, respectively. Cow – Soy (50:50) yoghourt had the highest (P<0.05) fat content, whereas the highest (P<0.05) protein content were recorded by Cow – Soy (50:50), Cow milk (100%) and Cow – Soy (20:80) yoghourts. Consistency of cow milk (100%) yoghourt was most preferred (P<0.05). Flavour of Cow – soy (50:50), cow milk (100%) and cow – tiger (50:50) yoghourts were Preferred (P<0.05). Colour and texture of cow – soy (50:50) and cow milk (100%) yoghourts were significantly preferred (P<0.05). Generally, yoghourts from cow milk (100%) and cow – soy (50:50) were most accepted (P<0.05). Total bacterial plate count of yoghurt formulations ranged from 1.3×10 10.5×10 CFU/ml and mould plate count from 2.4×10 8.7×10 CFU/ml. pH of yoghurt formulations 5 5 5 5 ranged from 3.97 4.75, whereas titratable acidity ranged from 0.09 1.13%. Therefore, yoghourt can be produced by partial substitution of cow milk with either soymilk or tiger nut.
Mental and Psycho-social Health and Quality-of-Life Before and After Cardiac Rehabilitation: A Prospective Cohort Study With Comparison to Specific Population Norms

Background. Data on mental health improvement after cardiac rehabilitation (CR) are contradicting. The aim was to examine the mental and psycho-social health of patients admitted to our rehabilitation center following hospital treatment for acute coronary syndrome, before and after multidisciplinary CR.Methods. Outcome was measured at admission and discharge by the 36-Item Short Form Survey (SF-36), the Symptom Checklist-90 Revised (SCL-90R), the Coping Strategy Questionnaire (CSQ) and the 6-minute-walking distance test. The patients’ health status was compared with norms of sex-, age- and comorbidity-matched data from the German general population. Score differences from norms were measured by standardized mean differences (SMDs); health changes were quantified by standardized effect sizes (ESs). Their importance for comprehensive assessment was quantified by explorative factor analysis.Results. Of n=70 patients followed-up (male: 79%; mean age: 66.6 years), 79% had ≥3 comorbidities. At baseline, SF-36 Physical functioning (SMD=–0.75), Role physical (–0.90), Social functioning (SMD=–0.44), and Role emotional (SMD=–0.45) were significantly worse than the norm. After CR, almost all scores significantly improved by ES=0.23 (SCL-90R Interpersonal sensitivity) to 1.04 (SF-36 Physical functioning). The strongest factor (up to 41.1% explained variance) for health state and change was the mental health domain, followed by function&pain (up to 26.3%). Conclusions. Normative deficits in physical and psycho-social health were reported at baseline. After CR, at follow-up, all scores, except phobia, showed significant improvement. The comprehensive measurement of bio-psycho-social health should not be limited to depression and anxiety but include, especially, the somatization and social participation dimensions.
The Role of Vacuum Fluctuations and Symmetry in the Hydrogen Atom in Quantum Mechanics and Stochastic Electrodynamics

Stochastic Electrodynamics (SED) has had success modeling black body radiation, the harmonic oscillator, the Casimir effect, van der Waals forces, diamagnetism, and uniform acceleration of electrodynamic systems using the stochastic zero-point fluctuations of the electromagnetic field with classical mechanics. However the hydrogen atom, with its 1/r potential remains a critical challenge. Numerical calculations have shown that the SED field prevents the electron orbit from collapsing into the proton, but, eventually the atom becames ionized. We look at the issues of the H atom and SED from the perspective of symmetry of the quantum mechanical Hamiltonian, used to obtain the quantum mechanical results, and the Abraham-Lorentz equation, which is a force equation that includes the effects of radiation reaction, and is used to obtain the SED simulations. We contrast the physical computed effects of the quantized electromagnetic vacuum fluctuations with the role of the real stochastic electromagnetic field.
Mechanisms of azole resistance in clinical isolates of Candida glabrata from two hospitals in China

Purpose: Candida glabrata has emerged as the second or third most common non-albicans species responsible for an increasing number of systemic infections. Moreover, its high-level of resistance to azole is associated with a high mortality rate. This study aimed to evaluate nosocomial infections and resistance characteristics of C. glabrata and to explore the mechanism of azole resistance in C. glabrata. Patients and methods: Fifty-nine clinical C. glabrata isolates were collected from two hospitals in China. The susceptibility of the strains to antifungal agents was determined by both the ATB Fungus 3 strip and CLSI M27 broth microdilution method. Efflux of rhodamine 6G was examined to evaluate the effects of efflux pumps. The expression levels of CgCDR1, CgCDR2, CgSNQ2, CgERG11, and CgPDR1 were examined by real-time PCR. The sequences of CgERG11 and CgPDR1 were determined by PCR-based DNA sequencing. Results: All 59 isolates of C. glabrata were susceptible to flucytosine and amphotericin B. Twelve (20.3%) isolates were determined to be fluconazole-resistant, whereas 13 (22.0%) and 27 (45.7%) isolates were categorized as non-wild-type for itraconazole and voriconazole, respectively. Efflux pumps in azole-resistant isolates showed stronger effects than those in azole-susceptible-dose dependent isolates, which is consistent with the significant upregulation of CgCDR1 and CgCDR2 (P<0.05), whereas no obvious differences were found for CgSNQ2, CgERG11, and CgPDR1 (P>0.05). Sequencing of CgERG11 showed no alteration favoring the hypothesis that CgERG11 is not involved in the azole resistance of C. glabrata. Four CgPDR1 missense mutations were found in azole-resistant isolates, of which the high frequency of the CgPDR1 mutation, A848V, has not been reported previously. Conclusion: Efflux pump function is the main mechanism of resistance to fluconazole in our collected clinical isolates of C. glabrata, and further studies of the related gene disruption and genome-wide expression are needed to verify the function.
Value-added intellectual capital and financial performance: evidence from Mauritian companies

PurposeThe purpose of this paper is to empirically assess the impact of value-added intellectual capital (VAIC) on the financial performance (FP) of companies in Mauritius.Design/methodology/approachThe research uses a dynamic panel vector error correction model (PVECM) which simultaneously allows for endogeneity and causality issues among the variables used.FindingsThe results show that VAIC enhances corporate FP, with a reported lower effect in the short run as compared to the long run. Other important determinants of firm’s performance are asset turnover, capital turnover and firm’s size. Leverage, on the other hand, is observed to be performance reducing in nature. FP of the companies is also a significant determinant of VAIC, implying reverse causal effects exist between the two variables of interest, namely, VAIC and FP.Research limitations/implicationsThe study can be enhanced by doing an industry-specific comparison of the impact of VAIC on FP for more insights.Practical implicationsIt is recommended that managers pay more attention to the role of firms’ stock of tangible and intangible assets, as this has a positive impact on firms’ FP. Also, the results may help to increase awareness of the importance of effective intellectual capital (IC) management within an organization. More so, as demonstrated by Ståhle et al. (2011), VAIC indicates the efficiency of the company’s labor and capital investments within firms in Mauritius. This study may, therefore, enable Mauritian firms to measure their IC efficiency and develop policies to promote and improve upon their intellectual potential to enhance firm’s performance.Originality/valueThe main theoretical contribution of this paper relates to the assessment and conceptualization of the bi-directional relationship between VAIC and FP. It confirmed that there are self-reinforcing feedback effects between VAIC and FP. Methodologically speaking, this paper investigates the VAIC–FP nexus in a dynamic setting using a dynamic panel data framework, namely, a PVECM which also allows for additional insights into the short- and long-run effects.
A Mathematical Model of Tritrophic Systems

The positive and negative differential values of x or y around equilibrium points give the behavior of the LV equations. If y is more significant than k1/k2, x decreases, and if y is minor, it increases. On the other hand, if x is more prominent than k3/k2, y increases, and if it is smaller, y decreases. Therefore, x and y oscillate around the equilibrium point; the solution to these equations are periodic (Figure 1) [1].
Developmentofa real-timePCRassay formonitoringanaerobic fungal and cellulolytic bacterial populationswithin the rumen

Traditional methods for enumerating and identifying microbial populations within the rumen can be time consuming and cumbersome. Methods that involve culturing and microscopy can also be inconclusive, particularly when studying anaerobic rumen fungi. A real-time PCR SYBR Green assay, using PCR primers to target total rumen fungi and the cellulolytic bacteria Ruminococcus flavefaciens and Fibrobacter succinogenes, is described, including design and validation. The DNA and crude protein contents with respect to the fungal biomass of both polycentric and monocentric fungal isolates were investigated across the fungal growth stages to aid in standard curve generation. The primer sets used were found to be target specific with no detectable cross-reactivity. Subsequently, the real-time PCR assay was employed in a study to detect these populations within cattle rumen. The anaerobic fungal target was observed to increase 3.6-fold from 0 to 12 h after feeding. The results also indicated a 5.4-fold increase in F. succinogenes target between 0 and 12 h after feeding, whereas R. flavefaciens was observed to maintain more or less consistent levels. This is the first report of a real-time PCR assay to estimate the rumen anaerobic fungal population.
Chapter 4 Sierpinski Carpet Fractal Patterned Dielectric Resonator Antenna ( SCFDRA )

4.1 Objective This chapter aims at investigating the behaviour of Sierpinski Carpet fractal dielectric resonator antenna. In the first half of this chapter, a wideband Sierpinski carpet patterned cylindrical Dielectric Resonator Antenna (DRA) operating in the X-Band is presented. This DRA is realized from low cost Teflon. Antenna design methodology is discussed along with its resonance and radiation characteristics. In the second half, a wideband Sierpinski Carpet fractal patterned rectangular Dielectric Resonator Antenna (DRA) operating in the X-Band which is characterised with Dielectric Waveguide Model (DWM) method is presented. For validation of simulated results, a prototype was realized. A comparison between conventional rectangular DRA and fractal shaped rectangular DRA of first iteration and second iteration and radiation characteristics of these structures are discussed.
Critical geometry of a thermal big bang

We explore the space of scalar-tensor theories containing two nonconformal metrics, and find a discontinuity pointing to a ``critical'' cosmological solution. Due to the different maximal speeds of propagation for matter and gravity, the cosmological fluctuations start off inside the horizon even without inflation, and will more naturally have a thermal origin (since there is never vacuum domination). The critical model makes an unambiguous, nontuned prediction for the spectral index of the scalar fluctuations: ${n}_{S}=0.96478(64)$. Considering also that no gravitational waves are produced, we have unveiled the most predictive model on offer. The model has a simple geometrical interpretation as a probe 3-brane embedded in an $E{\mathrm{AdS}}_{2}\ifmmode\times\else\texttimes\fi{}{E}_{3}$ geometry.
Effect of Environmental Optimism on Responsible Electricity Consumption with Price Concern as a Moderator

The study aimed to determine the effect of environmental optimism, as a cognitive–emotional factor, on the responsible use of electricity. Furthermore, it investigated the moderating effect of consumer concern on the price of electricity. An online survey was conducted on 345 young adults in Jakarta selected through the snowball sampling method. Data were analyzed using JASP version 15.0 and IBM SPSS Statistics version 23 reinforced with PROCESS macro. Simple linear regression analysis demonstrated that environmental optimism significantly explains the variance in electricity conservation behavior. The moderating effect of price concern was also substantiated by the result of the data analysis, thus the interaction between environmental optimism and dichotomous predictors of price concern (i.e. high vs low) was found to be statistically significant in moderating the effect of environmental optimism toward electricity conservation behavior. In conclusion, when consumers are initially dominated by price concern (a rational extrinsic motivator), then it reduces the effect of environmental optimism (an emotional intrinsic motivator) on responsible electricity consumption.
An interferometric determination of the refractive part of optical constants for carbon and silver across soft X-ray absorption edges

Interferometric, direct determinations of the f1 scattering factor near absorption edges in the soft x-ray range is demonstrated. The interferometric system, which is based on wave front division (no beam splitter) with plane mirrors only, produces a linear fringe pattern. The principle consists in direct measuring of the fringe shift occurring upon insertion of a sample into one interferometer arm, by means of a dedicated detection system. This provides the optical thickness, which in turn gives the f1 factor, knowing either the sample mass per unit surface, or the sample thickness and density. With the sample being probed in transmission under near normal incidence, the determination of f1 is not perturbed by the absorption part of the complex scattering factor. Therefore, f1 data obtained here can be said new and independent with respect to those obtained previously, in the sense that they are obtained from a new, purely experimental technique, and are neither deduced from nor perturbed by absorption.
A COMPARISON OF SOLID OXIDE FUEL CELL DESIGNS AS ENERGY SOURCE FOR THE ALL-ELECTRIC AIRCRAFT

The development of new aircraft system architectures for the so-called all-electric aircraft results in a highly increased electrical power demand from the systems. This electrical power can be provided by generators which convert engine shaft power into electrical power, and auxiliary power units on ground with engines off. Fuel cell systems may be an engine-independent alternative to this combination. Different system designs and alternative integration modes are presented in this paper and linked to their impact on aircraft performance. While the assessment of fuel cells on system level has been the object of many studies, the focus of this paper is the performance evaluation on aircraft level.
MANAGEMENT OF BRACHIAL PLEXUS MISSILE INJURIES

SUMMARY – Missile injuries are among the most devastating injuries in general traumatology. Traumatic brachial plexus injuries are the most difficult injuries in peripheral nerve surgery, and most complicated to be surgically treated. Nevertheless, missile wounding is the second most common mechanism of brachial plexus injury. The aim was to evaluate functional recovery after surgical treatment of these injuries. Our series included 68 patients with 202 nerve lesions treated with 207 surgical procedures. Decision on the treatment modality (exploration, neurolysis, graft repair, or combination) was made upon intraoperative finding. Results were analyzed in 60 (88.2%) patients with 173 (85.6%) nerve lesions followed-up for two years. Functional recovery was evaluated according to functional priorities. Satisfactory functional recovery was achieved in 90.4% of cases with neurolysis and 85.7% of cases with nerve grafting. Insufficient functional recovery was verified in ulnar and radial nerve lesions after neurolysis, and in median and radial nerve lesions when graft repair was done. We conclude that the best time for surgery is between two and four months after injury, except for the gunshot wound associated with injury to the surrounding structures, which requires immediate surgical treatment. The results of neurolysis and nerve grafting were similar.
On the Resistance of Nearest Neighbor to Random Noisy Labels

Nearest neighbor has always been one of the most appealing non-parametric approaches in machine learning, pattern recognition, computer vision, etc. Previous empirical studies partly shows that nearest neighbor is resistant to noise, yet there is a lack of deep analysis. This work presents the finite-sample and distribution-dependent bounds on the consistency of nearest neighbor in the random noise setting. The theoretical results show that, for asymmetric noises, k-nearest neighbor is robust enough to classify most data correctly, except for a handful of examples, whose labels are totally misled by random noises. For symmetric noises, however, k-nearest neighbor achieves the same consistent rate as that of noise-free setting, which verifies the resistance of k-nearest neighbor to random noisy labels. Motivated by the theoretical analysis, we propose the Robust k-Nearest Neighbor (RkNN) approach to deal with noisy labels. The basic idea is to make unilateral corrections to examples, whose labels are totally misled by random noises, and classify the others directly by utilizing the robustness of k-nearest neighbor. We verify the effectiveness of the proposed algorithm both theoretically and empirically.
Firehose and Mirror Instabilities in a Collisionless Shearing Plasma

Hybrid-kinetic numerical simulations of firehose and mirror instabilities in a collisionless plasma are performed in which pressure anisotropy is driven as the magnetic field is changed by a persistent linear shear $S$. For a decreasing field, it is found that mostly oblique firehose fluctuations grow at ion Larmor scales and saturate with energies $\sim$$S^{1/2}$; the pressure anisotropy is pinned at the stability threshold by particle scattering off microscale fluctuations. In contrast, nonlinear mirror fluctuations are large compared to the ion Larmor scale and grow secularly in time; marginality is maintained by an increasing population of resonant particles trapped in magnetic mirrors. After one shear time, saturated order-unity magnetic mirrors are formed and particles scatter off their sharp edges. Both instabilities drive sub-ion-Larmor--scale fluctuations, which appear to be kinetic-Alfven-wave turbulence. Our results impact theories of momentum and heat transport in astrophysical and space plasmas, in which the stretching of a magnetic field by shear is a generic process.