Miracle-dz/UniFAR-FTUs huggingface dataset:
Plasmonic Enhancement of Infrared Vibrational Signals: Nanoslits versus Nanorods

We report on systematic investigations of plasmonically active nanoslits as a beneficial substrate for surface-enhanced infrared absorption (SEIRA). Arranged in arrays, nanoslits with the proper geometry feature strong nanorod-like resonances in the infrared spectral range, as predicted by Babinet’s principle for the same geometrical dimensions. SEIRA enhancement as studied with a thin self-assembled molecular layer of octadecanethiol reaches the values obtained with nanorods if the slit geometry is optimized. We show by systematically examining the important parameters that the slit width has an especially strong influence on the near-field intensity and therefore on the SEIRA signal. Furthermore, the transversal and longitudinal couplings of nanoslits are studied. Compared to nanorod arrays, a stronger influence of the array periodicities on the plasmonic excitations is observed, which indicates coupling via surface plasmon polaritons. So the array periodicity could be further optimized toward higher SE.
Learning Unknown Service Rates in Queues: A Multiarmed Bandit Approach

Traditional scheduling problems in stochastic queueing systems assume that the statistical parameters are known a priori. In ''Learning unknown service rates in queues: A multiarmed bandit approach'', Krishnasamy, Sen, Johari, and Shakkottai consider the problem of online scheduling in a parallel-server system when the statistical parameters are unknown. They study this question in the stochastic multiarmed bandits framework with the queue length as the performance objective. In contrast to the classic stochastic multiarmed bandits problem, where the regret scales logarithmically with time, the authors show that the queue regret (difference in expected queue length between a bandit algorithm and a genie policy) exhibits a more complex behavior. It grows logarithmically in the initial stage and eventually decays almost inversely with time. This remarkable behavior is explained through the analysis of regenerative cycle lengths, which shorten with time as the bandit algorithm learns to stabilize the queues.
Prediction tool for renal adaptation after living kidney donation using interpretable machine learning

Introduction Post-donation renal outcomes are a crucial issue for living kidney donors considering young donors’ high life expectancy and elderly donors’ comorbidities that affect kidney function. We developed a prediction model for renal adaptation after living kidney donation using interpretable machine learning. Methods The study included 823 living kidney donors who underwent nephrectomy in 2009–2020. AutoScore, a machine learning-based score generator, was used to develop a prediction model. Fair and good renal adaptation were defined as post-donation estimated glomerular filtration rate (eGFR) of ≥ 60 mL/min/1.73 m2 and ≥ 65% of the pre-donation values, respectively. Results The mean age was 45.2 years; 51.6% were female. The model included pre-donation demographic and laboratory variables, GFR measured by diethylenetriamine pentaacetate scan, and computed tomography kidney volume/body weight of both kidneys and the remaining kidney. The areas under the receiver operating characteristic curve were 0.846 (95% confidence interval, 0.762–0.930) and 0.626 (0.541–0.712), while the areas under the precision-recall curve were 0.965 (0.944–0.978) and 0.709 (0.647–0.788) for fair and good renal adaptation, respectively. An interactive clinical decision support system was developed.1 Conclusion The prediction tool for post-donation renal adaptation showed good predictive capability and may help clinical decisions through an easy-to-use web-based application.
A Framework of Granular Computing Clustering Algorithms

A framework of granular computing clustering algorithms is proposed in the paper. Firstly, granules are represented as the normal forms, such the diamond granule in 2domensional space and hyperdiamond granule in N-dimensional space, sphere granule in 2-dimensional space and hypersphere granule in N-dimensional space. Secondly, operations between two granules are designed to realize the transformation between two spaces with different granularities. Thirdly, the threshold of granularity is used to control the join process between two granules. The performance of granular computing algorithms is evaluated by the experimental results on the data sets selected from machine learning repository.
Effects of different transcranial magnetic stimulations on neuropathic pain after spinal cord injury

Introduction Repetitive transcranial magnetic stimulation (rTMS) is an effective non-invasive cortical stimulation technique in the treatment of neuropathic pain. As a new rTMS technique, intermittent theta burst stimulation (iTBS) is also effective at relieving pain. We aimed to establish the pain-relieving effectiveness of different modalities on neuropathic pain. The study was conducted in individuals with spinal cord injury (SCI) and different modalities of rTMS. Methods Thirty-seven individuals with SCI were randomly allocated to three groups, in which the “iTBS” group received iTBS, the “rTMS” group received 10 Hz rTMS, and the “iTBS + rTMS” group received iTBS and 10 Hz rTMS successively of the primary motor cortex 5 days a week for 4 weeks, and they all underwent the full procedures. The primary outcome measure was change in the visual analog scale (VAS), and the secondary outcomes were measured using the Hamilton Rating Scale for Depression (HAM-D) and the Pittsburgh Sleep Quality Index (PSQI). All the outcomes were evaluated at 1 day before stimulation (baseline), 1 day after the first week of stimulation (S1), and 1 day after the last stimulation (S2). Results The VAS scores showed significant pain improvement after 4 weeks of stimulation (p = 0.0396, p = 0.0396, and p = 0.0309, respectively) but not after 1 week of stimulation. HAM-D scores declined, but the decreases were not significant until 4 weeks later (p = 0.0444, p = 0.0315, and p = 0.0447, respectively). PSQI scores were also significantly decreased after 4 weeks of stimulation (p = 0.0446, p = 0.0244, and p = 0.0088, respectively). Comparing the three modalities, VAS, HAM-D, and PSQI scores at S1 showed no differences, and, at S2, VAS scores showed significant differences (p = 0.0120; multiple comparisons showed significant differences between iTBS and iTBS + rTMS, p = 0.0091), while the HAM-D and PSQI scores showed no differences. Discussion The primary and secondary outcomes all showed significant improvement, indicating that the three different modalities were all effective at relieving the pain. However, not all the three stimulations were of same effectiveness after treatment; there were statistical differences in the treatment of neuropathic pain between iTBS as a priming stimulus and as a single procedure.
Development and validation of a nomogram model for predicting unfavorable functional outcomes in ischemic stroke patients after acute phase

Introduction Prediction of post-stroke functional outcome is important for personalized rehabilitation treatment, we aimed to develop an effective nomogram for predicting long-term unfavorable functional outcomes in ischemic stroke patients after acute phase. Methods We retrospectively analyzed clinical data, rehabilitation data, and longitudinal follow-up data from ischemic stroke patients who underwent early rehabilitation at multiple centers in China. An unfavorable functional outcome was defined as a modified Rankin Scale (mRS) score of 3–6 at 90 days after onset. Patients were randomly allocated to either a training or test cohort in a ratio of 4:1. Univariate and multivariate logistic regression analyses were used to identify the predictors for the development of a predictive nomogram. The area under the receiver operating characteristic curve (AUC) was used to evaluate predictive ability in both the training and test cohorts. Results A total of 856 patients (training cohort: n = 684; test cohort: n = 172) were included in this study. Among them, 518 patients experienced unfavorable outcomes 90 days after ischemic stroke. Trial of ORG 10172 in Acute Stroke Treatment classification (p = 0.024), antihypertensive agents use [odds ratio (OR) = 1.86; p = 0.041], 15-day Barthel Index score (OR = 0.930; p < 0.001) and 15-day mRS score (OR = 13.494; p < 0.001) were selected as predictors for the unfavorable outcome nomogram. The nomogram model showed good predictive performance in both the training (AUC = 0.950) and test cohorts (AUC = 0.942). Conclusion The constructed nomogram model could be a practical tool for predicting unfavorable functional outcomes in ischemic stroke patients underwent early rehabilitation after acute phase.
Existence of magic 3‐dimensional rectangles

Since the complete solution for the existence of magic 2‐dimensional rectangles in 1881, much attention has been paid on the existence of magic l‐dimensional rectangles for l≥3 . The existence problem for magic l‐dimensional rectangles with even sizes has been solved completely for all integers l≥3 . However, very little is known for the existence of magic l‐dimensional rectangles ( l≥3 ) with odd sizes except for some families and a few sporadic examples. In this paper, we focus our attention on the existence of magic 3‐dimensional rectangles and prove that the necessary conditions for the existence of magic 3‐dimensional rectangles are also sufficient. Our construction method is mainly based on a new concept, symmetric zero‐sum subset partition, which plays a crucial role in the recursive constructions of magic 3‐rectangles similar to that of PBD in the PBD‐closure construction in combinatorial design theory.
Morphological features and water solubility of iron in aged fine aerosol particles over the Indian Ocean

Abstract. Atmospheric transport of iron (Fe) in fine anthropogenic aerosol particles is an important route of soluble Fe supply from continental areas to remote oceans. To elucidate Fe properties of aerosol particles over remote oceans, we collected atmospheric aerosol particles over the Indian Ocean during the RV Hakuho Maru KH-18-6 cruise. After aerosol particles were collected using a cascade impactor, particles of 0.3–0.9 µm aerodynamic diameter on the sample stage were analyzed using transmission electron microscopy (TEM) with an energy-dispersive X-ray spectrometry analyzer. The particle shape and composition indicated that most particles collected north of the Equator were composed mainly of ammonium sulfate. Regarding the particle number fraction, 0.6 %–3.0 % of particles contained Fe, which mostly co-existed with sulfate. Of those particles, 26 % of Fe occurred as metal spheres, often co-existing with Al or Si, regarded as fly ash; 14 % as mineral dust; and 7 % as iron oxide aggregates. Water dialysis analyses of TEM samples indicated Fe in spherical fly ash as being almost entirely insoluble and Fe in other morphological-type particles as being partly soluble (65 % Fe mass on average). Global model simulations mostly reproduced observed Fe mass concentrations in particulate matter with a diameter of less than 2.5 µm (PM2.5) collected using a high-volume air sampler, including their north–south contrast during the cruise. In contrast, a marked difference was found between the simulated mass fractions of Fe mineral sources and the observed Fe types. For instance, the model underestimated anthropogenic aluminosilicate (illite and kaolinite) Fe contained in matter such as fly ash from coal combustion. Our observations revealed multiple shapes and compositions of Fe minerals in particles over remote ocean areas and further suggested that their solubilities after aging processes differ depending on their morphological and mineral types. Proper consideration of such Fe types at their sources is necessary for accurately estimating atmospheric Fe effects on marine biological activity.
On the vibration analysis of off-road vehicles: Influence of terrain deformation and irregularity

Surface irregularity acts as a major excitation source in off-road driving that induces vibration of the vehicle body through the tire assembly and the suspension system. When adding ground deformability, this excitation is modulated by the soil properties and operating conditions. The underlying mechanisms that govern ground behavior can be explained and modeled drawing on Terramechanics. Based on this theory, a comprehensive quarter-car model of off-road vehicle is presented that takes into account tire/soil interaction. The model can handle the general case of compliant wheel rolling on compliant ground and it allows ride and road holding performance to be evaluated in the time and frequency domain. An extensive set of simulation tests is included to assess the impact of various surface roughness and ground deformability through a parameter study, showing the potential of the proposed model to describe the behavior of off-road vehicles for design and performance optimization purposes.
Wildlife restoration in Nepal: tracking the conservation translocations in the country

Negative consequences of human impacts on biodiversity are undisputable and inadequate efforts in managing biodiversity have been realized across the globe. The present biodiversity crisis, including burgeoning effects of climate change, therefore, has warranted restoration actions in place. Conservation translocation, one of the effective measures of restoration, involves the individuals of species deliberate movement from one habitat to another, particularly animal species. Nepal has been practicing the conservation translocations for more than four decades. However, details of conservation translocation events and outcomes are not well documented. This article aims to explore the status and issues of conservation translocation in Nepal. For the purpose, we reviewed seven protected area management plans and nine species conservation action plans available in public domain along with related peer reviewed journal articles. We documented the conservation translocation of Blackbuck, Gharials, Swamp deer, Greater One Horned Rhino, Elongated tortoise, Narrow Headed Soft Shell Turtle, Wild Water Buffalo and Vulture. Adoption of feeble adaptive management framework and ad hoc approach of wildlife translocation has left many rooms for improvement in the translocation strategies of Nepal. This is largely exemplified by the improvement required in Vulture Breeding Center, Swamp deer and Wild water buffalo translocations to Chitwan National Park, and Blackbuck translocation to Bardia National Park. For many species, data and information are limited to evaluate the wildlife restoration outcomes independently.
Predicting The Share of Tourism Revenues In Total Exports

Tourism revenues are a significant source of income under the current account service item of countries. These revenues are not included in exports, despite being compared with the export revenues of the countries and in economics the ratio of tourism revenues to export revenues is used as an indicator. In developing economies, tourism revenues play a role in closing the current account deficit. The prediction of this rate in countries with foreign trade deficit is important in developing tourism, export and import policies for the future. In this study, multiple linear regression method (MLR), one of the traditional methods, and the artificial neural network method (ANN), one of the machine learning methods were used to estimate the rate of tourism revenues of the sample country Turkey to its export revenues. In the model of the study covering 2004-2020 period, the number of tourists received, total income from tourism, average expenditure by tourists per capita, population, total export revenue, growth rate, Euro/TL and US Dollar/TL rates were chosen as independent variables. As a result of the study, the R2 value was found to be 91.7% for ANN and 90.8% for MLR which were very close to the ideal value. According to the predicts made on the model developed based on this, the rate of Turkey's tourism income to total export income in 2025 is estimated as 31.83% according to ANN; 32.73% according to MLR while in 2030, it is estimated to be 33.25% according to ANN and 36.78% according to MLR.
Femtosecond laser ablated pyramidal fiber taper-SERS probe with laser-induced silver nanostructures

A highly sensitive pyramid-shaped SERS fiber probe (P-Probe) has been first realized by a fabrication method-femtosecond (fs) laser ablation. Using the laser-induced deposition method, silver nanostructures are grown on the pyramidal fiber with the controlled cover density by an inline power meter in real time. A reduction power ratio, the ratio of power after induction to the power before induction, is introduced to optimize the laser reduction. The P-Probe performances with different reduction power ratios show that, the induction power ratio 60% is the optimized value for the enhancement of SERS signal. The sensitivity of the fiber SERS probe is down to 10−9 M with Rhodamine 6G being target molecules. The proposed pyramid-shaped SERS fiber probe can be an alternative tool to detect the biomolecules of a single cell in biology sensing applications.
Net Energy Value of a Cassava Chip Ration for Lactation in Holstein–Friesian Crossbred Dairy Cattle Estimated by Indirect Calorimetry

Simple Summary The net energy value of feedstuff for lactation is a critical piece of data for the development of the dairy feeding system toward improving animal productivity and sustainability. Cassava (Manihot esculenta Crantz), a tuber crop in the tropics, is available year-round for Thai cassava starch and the export feed industry. It contains abundant digestible starch, so its nutritive value makes it suitable as an alternative energy feed source for ruminants. Determination of the net energy value of cassava chips for lactation will allow for the more precise formulation of diets that are optimal for dairy cows. This study aimed to (1) evaluate the effects of cassava, including in the diets offered to mid-lactation dairy cows, on production performance and (2) determine the net energy for lactation content of cassava chips. The findings indicate that increasing the cassava chips in the diets of Holstein–Friesian crossbred dairy cows could result in improved nutrient intake, digestibility, energy balance status, milk yield, and milk composition without the effect on enteric methane yield and intensity. The net energy for the lactation of cassava chips was estimated as 8.03 MJ/kg DM. Abstract The objectives of this research were to (1) determine the feed intake, digestibility, and energy utilization and (2) estimate the net energy value of cassava chips consumed by lactating dairy cows. Four multiparous Holstein–Friesian crossbred cows at 139 ± 33 (mean ± SD) day in milk were assigned according to a 4 × 4 Latin square design with four periods. The four treatments included a diet substituted with cassava chips on a 0%, 12%, 24%, and 36% dry matter (DM) basis in the basal diet. Indirect calorimetry with a head cage respiration system was used to determine nutrient and energy utilization. Increasing the number of cassava chips in the diet resulted in a linear increase (p < 0.05) in nutrient intake and digestibility but a linear decrease (p < 0.01) in crude protein (CP) and fiber. The enteric methane yield and intensity were not affected (p > 0.05), while energy was lost as feces and urine reduced linearly (p < 0.05). Milk yield and milk composition (protein, fat, lactose) also increased linearly (p < 0.05). The net energy requirement for the maintenance of the lactating cows was estimated as 327 kJ/kg of metabolic body weight, and the efficiency of metabolizable energy used for lactation was 0.66. The estimated net energy value of cassava chips for lactation was 8.03 MJ/kg DM.
Towards ultrafast subnanojoule solitonic nonlinear directional coupler based on soft glass dual-core photonics crystal fibers

We demonstrate narrow band spectral intensity switching in dual-core photonic crystal fibers made of highly nonlinear glass under femtosecond excitation. The fibers expressed dual-core asymmetry, thus the slow and fast fiber cores were unambiguously distinguished according to their dispersion profiles. The asymmetry effect on the dual-core propagation in anomalous dispersion region was studied both experimentally and numerically. The experimental study was carried out using femtosecond laser amplifier system providing tunable pulses in range of 1500 nm - 1800 nm. The obtained results unveiled, that it is possible to improve nonlinearly the coupling between the two waveguides by excitation of the fast fiber core. The results were obtained in regime of high-order soliton propagation and were verified numerically by the coupled generalized nonlinear Schrödinger equations model. The spectral analysis of the radiation transferred to the non-excited core revealed the role of effects such as third order dispersion, soliton compression and spectral dependence of the coupling efficiency. The simulation results provide reasonable agreement with the experimentally observed spectral evolutions in the both fiber cores. Under 1800 nm excitation, narrow band spectral intensity switching was registered with contrast of 23 dB at 10 mm fiber length by changing the excitation pulse energy in sub-nanojoule range.
Fourier ptychography for high space-bandwidth product microscopy

Abstract Fourier ptychography is a novel imaging technique with high space-bandwidth product (SBP) on the scale of gigapixel, and has been successfully applied for high-resolution and large field-of-view (FOV) microscopy, termed Fourier ptychographic microscopy (FPM). FPM utilizes a low-numerical-aperture objective lens to capture multiple large FOV but low-resolution images under angularly varying illumination, and uses phase-retrieval algorithms to reconstruct the sample’s high-resolution amplitude and phase information. FPM is advantageous over conventional high SBP microscopy techniques in many aspects, including no mechanical scanning, computational acquisition of both amplitude and phase, extended depth of focus, long working distance, and high compatibility with current microscopes. In this paper, we review FPM with its principles, multiple techniques to improve its performance, and its various applications and extensions.