Miracle-dz/UniFAR-FTUs huggingface dataset:
Integration of Spectral Reflectance Indices and Adaptive Neuro-Fuzzy Inference System for Assessing the Growth Performance and Yield of Potato under Different Drip Irrigation Regimes

Simultaneous and timely assessment of growth and water status-related plant traits is critical for precision irrigation management in arid regions. Here, we used proximal hyperspectral sensing tools to estimate biomass fresh weight (BFW), biomass dry weight (BDW), canopy water content (CWC), and total tuber yield (TTY) of two potato varieties irrigated with 100%, 75%, and 50% of the estimated crop evapotranspiration (ETc). Plant traits were assessed remotely using published and newly constructed vegetation and water spectral reflectance indices (SRIs). We integrated genetic algorithm (GA) and adaptive neuro-fuzzy inference system (ANFIS) models to predict the measured traits based on all SRIs. The different plant traits and SRIs varied significantly (p < 0.05) between the three irrigation regimes for the two varieties. The values of plant traits and majority SRIs showed a continuous decrease from the 100% ETc to the 50% ETc. Water-SRIs performed better than vegetation-SRIs for estimating the four plant traits. Almost all indices of the two SRI types had a weak relationship with the four plant traits (R2 = 0.00–0.37) under each irrigation regime. However, the majority of vegetation-SRIs and all water-SRIs showed strong relationships with BFW, CWC, and TTY (R2 ≥ 0.65) and moderate relationships with BDW (R2 ≥ 0.40) when the data of all irrigation regimes and varieties were analyzed together for each growing season or the data of all irrigation regimes, varieties, and seasons were combined together. The ANFIS-GA model predicted plant traits with satisfactory accuracy in both calibration (R2 = 1.0) and testing (R2 = 0.72–0.97) modes. The results indicate that SRI-based ANFIS models can improve plant trait estimation. This analysis also confirmed the benefits of applying GA to ANFIS to estimate plant responses to different growth conditions.
The effectiveness of electroneuromyography in the early diagnosis of diabetic foot development

Objective: Diabetic foot is one of the first cause of lower extremity amputation. The aim of this study is to determine which of the nerve conduction disorders may be used predominantly for early diagnosis of diabetic foot development in the follow-up of diabetic patients. Material and Method: The study consists of 3 different groups (150) of patients diagnosed with type 2 diabetes (DM). 1. Group; 50 patients with diabetic foot complications (DA+), 2. Group; 50 patients without diabetic foot complications and with polyneuropathy (DA-/PNP+), 3. Group; 50 patients without diabetic foot complications and without polyneuropathy (DA-/PNP-). Diabetic foot wounds were grouped by pedis classification. Findings: Age, sex, diabetes duration, blood glucose, HbA1c values and electroneuromyography (ENMG) for nerve amplitude, velocity and latancy results were compared among the groups. A significant statistical difference was found between three groups when age, sex, HgbA1c, fasting blood glucose, diabetes duration were evaluated (p 0.05). Peroneal nerve conduction velocity was lowest in the DA+ group. This factor was considered as a risk factor for DA development. Conclusions: In conclusion, the slowdown in peroneal nerve conduction velocity and the increase in diabetes duration were the primary risk factors for diabetic foot development, and the decrease in tibial nerve velocity was also considered as significant. This study showed that the involvement of motor nerve conduction in the lower extremity was considered as a signal for diabetic foot development.
Colonnade: A Reconfigurable SRAM-Based Digital Bit-Serial Compute-In-Memory Macro for Processing Neural Networks

This article (Colonnade) presents a fully digital bit-serial compute-in-memory (CIM) macro. The digital CIM macro is designed for processing neural networks with reconfigurable 1–16 bit input and weight precisions based on bit-serial computing architecture and a novel all-digital bitcell structure. A column of bitcells forms a column MAC and used for computing a multiply-and-accumulate (MAC) operation. The column MACs placed in a row work as a single neuron and computes a dot-product, which is an essential building block of neural network accelerators. Several key features differentiate the proposed Colonnade architecture from the existing analog and digital implementations. First, its full-digital circuit implementation is free from process variation, noise susceptibility, and data-conversion overhead that are prevalent in prior analog CIM macros. A bitwise MAC operation in a bitcell is performed in the digital domain using a custom-designed XNOR gate and a full-adder. Second, the proposed CIM macro is fully reconfigurable in both weight and input precision from 1 to 16 bit. So far, most of the analog macros were used for processing quantized neural networks with very low input/weight precisions, mainly due to a memory density issue. Recent digital accelerators have implemented reconfigurable precisions, but they are inferior in energy efficiency due to significant off-chip memory access. We present a regular digital bitcell array that is readily reconfigured to a 1–16 bit weight-stationary bit-serial CIM macro. The macro computes parallel dot-product operations between the weights stored in memory and inputs that are serialized from LSB to MSB. Finally, the bit-serial computing scheme significantly reduces the area overhead while sacrificing latency due to bit-by-bit operation cycles. Based on the benefits of digital CIM, reconfigurability, and bit-serial computing architecture, the Colonnade can achieve both high performance and energy efficiency (i.e., both benefits of prior analog and digital accelerators) for processing neural networks. A test-chip with $128 \times 128$ SRAM-based bitcells for digital bit-serial computing is implemented using 65-nm technology and tested with 1–16 bit weight/input precisions. The measured energy efficiency is 117.3 TOPS/W at 1 bit and 2.06 TOPS/W at 16 bit.
Wind Turbine Fault Detection Using Highly Imbalanced Real SCADA Data

Wind power is cleaner and less expensive compared to other alternative sources, and it has therefore become one of the most important energy sources worldwide. However, challenges related to the operation and maintenance of wind farms significantly contribute to the increase in their overall costs, and, therefore, it is necessary to monitor the condition of each wind turbine on the farm and identify the different states of alarm. Common alarms are raised based on data acquired by a supervisory control and data acquisition (SCADA) system; however, this system generates a large number of false positive alerts, which must be handled to minimize inspection costs and perform preventive maintenance before actual critical or catastrophic failures occur. To this end, a fault detection methodology is proposed in this paper; in the proposed method, different data analysis and data processing techniques are applied to real SCADA data (imbalanced data) for improving the detection of alarms related to the temperature of the main gearbox of a wind turbine. An imbalanced dataset is a classification data set that contains skewed class proportions (more observations from one class than the other) which can cause a potential bias if it is not handled with caution. Furthermore, the dataset is time dependent introducing an additional variable to deal with when processing and splitting the data. These methods are aimed to reduce false positives and false negatives, and to demonstrate the effectiveness of well-applied preprocessing techniques for improving the performance of different machine learning algorithms.
An assessment of the carbon footprint of restaurants based on energy consumption: A case study of a local pizza chain in Turkey

ABSTRACT This study calculated the carbon footprint of a local pizza restaurant chain in Izmir, Turkey, based on its operational energy consumption. In Turkey, country-specific greenhouse gas (GHG) emissions have not yet been determined and based on legislation, only industrial companies with high emissions are compelled to develop GHG inventory reporting. The study faced several limitations. First, suppliers lack usable carbon footprint information. Second, there are three other local pizza chains in Izmir, which are similar to the one in this case study having more than 10 branches and offering take-home delivery. However, it was also not possible to obtain data from them to make comparisons. Finally, since the case restaurant did not integrate environmental management systems into its organizational structure, it was not possible to use carbon emission assesments under ISO 14064 or PAS 2050. Consequently, because the only reliable data were for the restaurant’s energy consumption our results should be interpreted cautiously when comparing with other types of restaurants in other countries and unavoidable errors should be considered. The Tier 1 approach of the Intergovernmental Panel on Climate Change (IPCC) was used to calculate the restaurant’s carbon footprint. Five years of data (2015–2020) were collected from utility bills and purchasing records, which were then converted into CO2 equivalents. Based on this energy consumption data, the restaurant’s carbon footprint was calculated as 1,919.818 tCO2e. To offset this, afforestation was proposed. Specifically, 3,062 trees would have to be planted to make its operations carbon neutral.
A Low-Cost Sensor for Detecting Illicit Discharge in Sewerage

The presence of illicit discharges in sewerage systems generates an important impact in wastewater treatment plants and the ecosystem. In this paper, we present two prototypes for monitoring the presence of solids in wastewater and to study the effect of the water height. The prototypes are based on color and infrared LEDs and two photosensors located in the prototypes at 0° and 180° degrees. When the photosensor is located at 180°, all color LEDs present a good range of output voltage (approximately 5 V to 0 V) and good R2. However, for the typical concentration of solids in wastewater, the prototypes do not work correctly. When the photosensor is located in the prototypes the LEDs, yellow, red, and white have a good operation with voltage differences of 1.73 V, 1.76 V, and 1.13 V in P1 and 1.58 V, 1.84 V, and 1.35 V in P2, respectively. We calculate the mathematical model with the heights and solid concentration. The mathematical models which do not consider height present good R2. In conclusion, when the photosensor is located in the prototype, the height does not have an important effect and can detect the illicit discharge of solids. When the photosensor is located at 180°, it can be used for water with important changes in solid concentrations.
Phytochemical Profile and In Vitro Antioxidant Properties of Essential Oils from Powder Fractions of Eucalyptus camaldulensis Leaves

Dried leaves of Eucalyptus camaldulensis were finely grinded and fractionated by sieving into four granulometric classes ( 355 μm). The obtained powder fractions were used for essential oil (EO) extraction by hydrodistillation and their phytochemical profile and in vitro antioxidant activities were evaluated. The mother powder (unsieved powder) was used for comparison. Particle size exerted a significant influence (p < 0.05) on the phytochemical composition and in vitro antioxidant properties of the EOs. Comparatively, the mother powder had the highest contents of α-pinene (55.6%), camphene (3.4%) and limonene (3.7%), while 1,8-cineole (26.6% and 22.4%), exo-fenchol (5.6% and 3.5%), α-campholenol (4.2% and 3.4%), L-trans-pinocarveol (5.5% and 2.7%), L-borneol (12.6% and 6.8%) and α-terpineol (16.4% and 7.6%) are the main compounds of EOs from the <100 μm and 100 - 200 μm fractions, respectively. The antioxidant activities of the EOs revealed higher radical-scavenging activities DPPH (90.62% and 70.46%) and ABTS (89.59% and 73.31%) for finer fractions (<100 μm and 100 - 200 μm, respectively). The best reducing power (36.15% and 34.27%) were also found in these finer powder fractions which improved by more than 2 times the value of mother powder (reducing power of 17.01%). These results suggest that grinding followed by sieve fractionation concentrates the majority of antioxidant phytochemicals in the EOs of the finer powder fractions of E. camaldulensis leaves. Finer powders could be used as functional ingredients in food formulations for the management of chronic diseases.
The initiation and progression of damage in composite overwrapped pressure vessels subjected to contact loads

In order to investigate the residual strength of composite overwrapped pressure vessels subjected to impact loads, an extensive experimental study has been performed. The vessels are loaded up to different mechanical work levels (quasi-static) or with various impact energies (dynamic). After loading, the emerged damage in the pressure vessel is examined using computed tomography scans. The tests of vessels up to various energies enable us to visualize the initiation and progressive growth of damage. The overall influence of the damage is subsequently quantified by means of a burst pressure test. Accordingly, the reduction of burst pressure can be used to evaluate the global severity of the observed damage in the computed tomography scan. From the experiments, it is concluded that the first failure mechanisms, that is, delaminations, do not cause a meaningful reduction of the burst pressure. Shear bands, on the other hand, which are formed thereafter, do induce a significant decrease of the residual strength.
Children’s Spontaneous Additive Strategy Relates to Multiplicative Reasoning

Abstract We examine a hypothesis implied by Steffe’s constructivist model of children’s numerical reasoning: a child’s spontaneous additive strategy may relate to a foundational form of multiplicative reasoning, termed multiplicative double counting (mDC). To this end, we mix quantitative and qualitative analyses of 31 fourth graders’ responses during clinical, task-based interviews. All participants spontaneously used one of three additive strategies—counting-on, doubling, or break-apart-make-ten (BAMT)—to correctly solve an addition word problem (8 + 7). We found between-group differences, with asymmetric association of those ordinal variables. We found counting-on to be mainly related to premultiplicative reasoning and BAMT to mDC reasoning. We discuss the theoretical significance and implications of this corroboration of Steffe’s model.
THE ASSOCIATION OF CALF CIRCUMFERENCE AND ALL-CAUSE, CARDIOVASCULAR AND CEREBROVASCULAR MORTALITY: RESULTS FROM THE NATIONAL HEALTH AND NUTRITION EXAMINATION SURVEYS

Studies on the association between calf circumference (CC) and mortality has been limited. Therefore, we examined the association between CC and all-cause, cardiovascular and cerebrovascular mortality in the present study.The data was retrieved from the 1999-2006 National Health and Nutritional Examination Surveys (NHANES), composing of 20, 214 individuals aged ≥ 18 years with CC being measured. We performed multivariate Cox regression models to examine the associations, then stratified the regression models into subgroups to test for interactions.Among 20, 214 participants, 47.25% were men and the mean age was 45.8 years. In the fully adjusted model, each 1 cm increment in CC was inversely associated with the risk of all-cause mortality (HR = 0.92, 95%CI = 0.90-0.94, P < 0.0001) and cardiovascular mortality (HR = 0.90, 95%CI = 0.84-0.97, P = 0.0056). Meanwhile, the highest quartile of CC had 50% (HR = 0.50, 95%CI = 0.40-0.64, P trend < 0.001) lower risk of all-cause mortality and 57% (HR = 0.43, 95%CI = 0.21-0.88, P trend = 0.045) lower risk of cardiovascular mortality, compared to the lowest quartile of CC. For cerebrovascular mortality, CC did not have significant associations with mortality.Our results suggested an independently inverse association between CC and all-cause and cardiovascular mortality.
Cryogenic ion trapping for next generation quantum technologies

Quantum technology has made great strides in the last two decades with trapped ions demonstrating all the necessary building blocks for a quantum computer. While these proof of principle experiments have been demonstrated, it still remains a challenging task to scale these experiments down to smaller systems. In this thesis I describe the development of technology towards scalable cryogenic ion trapping and quantum hybrid systems. I first discuss the fundamentals of ion trapping along with the demonstration of ion trapping on a novel surface electrode ion trap with a ring shaped architecture. I then present the development of a cryogenic vacuum system for ion trapping at ~4 K, which utilizes a closed cycle Gifford McMahon cryocooler with a helium gas buffered ultra-low vibration interface to mechanically decouple a ultra-high vacuum system. Ancillary technologies are also presented, including a novel in-vacuum superconducting rf resonator, low power dissipation ceramic based atomic source oven and an adaptable in-vacuum permanent magnet system for long-wavelength based quantum logic. The design and fabrication of microfabricated surface ion traps toward quantum hybrid technologies are then presented. A superconducting ion trap with an integrated high quality factor microwave cavity and vertical ion shuttling capabilities is described. The experimental demonstration of the cavity is also presented with quality factors of Q6~6000 and Q~15000 for superconducting niobium nitride and gold based cavities respectively, which are the highest demonstrated for microwave cavities integrated within ion trapping electrode architectures. An ion trap with a multipole electrode geometry is then presented, which is capable of trapping a large number of ions simultaneously. The homogeneity of five individual linear trapping regions are optimized and the design for the principle axis rotation of each linear region is presented. An overview of microfabrication techniques used for fabricating surface electrode ion traps is then presented. This includes the detailed microfabrication procedure for ion traps designed within this thesis. A scheme for the integration of ion trapping and superconducting qubit systems as a step towards the realization of a quantum hybrid system is then presented. This scheme addresses two key diffculties in realizing such a system; a combined microfabricated ion trap and superconducting qubit architecture, and the experimental infrastructure to facilitate both technologies. Solutions that can be immediately implemented using current technology are presented. Finally, as a step towards scalability and hybrid quantum systems, the interaction between a single ion and a microwaves field produced from an on chip microwave cavity is explored. The interaction is described for the high-Q microwave cavity designed in this thesis and a 171Yb+ion. A description of the observable transmission from the cavity is described and it is shown that the presence of a single ion can indeed be observed in the emission spectrum of high-Q microwave cavity even in the weak coupling regime.
Average Modeling of a Dual-Half-Bridge Converter Modulated With Three Degrees of Freedom

This article presents average modeling of a dual-half-bridge (DHB) dc–dc converter operated with independent control over phase shift, the primary-side duty cycle, and the secondary-side duty cycle. All six possible working modes and their corresponding power transfer characteristics are derived. State-space average models of the working modes are developed, and a corresponding closed-loop control scheme is proposed to regulate the power flow and lower/upper arm voltage split at both sides of the transformer independently. In addition, a transformer minimum rms current operation rule is presented. Finally, experimental results are presented to support the theoretical analysis.
Swinging for the Fences Versus Advancing the Runner: Culture, Motivation, and Strategic Decision Making

This research investigated cross-cultural differences in strategic risky decisions in baseball—among professional baseball teams in North America and Japan (Study 1) and among baseball fans in the United States and Japan (Study 2—preregistered). Study 1 analyzed archival data from professional baseball leagues and demonstrated that outcomes reflecting high risk-high payoff strategies were more prevalent in North America, whereas outcomes reflecting low risk-low payoff strategies were more prevalent in Japan. Study 2 investigated fans’ strategic decision making with a wider range of baseball strategies as well as an underlying reason for the difference: approach/avoidance motivational orientation. European American participants preferred high risk-high payoff strategies, Japanese participants preferred low risk-low payoff strategies, and this cultural variation was explained by cultural differences in motivational orientation. Baseball, which exemplifies a domain where strategic decision making has observable consequences, can demonstrate the power of culture through the actions and preferences of players and fans alike.
Ciklodextrinek és sztatinok kölcsönhatásának in vitro vizsgálatai

Cyclodextrins (CDs) are cyclic oligosaccharides, capable of forming inclusion complexes with hydrophobic molecules in aqueous solution and therefore, of improving the bioavailability of many drugs. They are biocompatible with living cells and do not cause toxic side effects. In this study, interactions in aqueous solutions between chemically different CDs and lovastatin and simvastatin, respectively, were investigated. It was found that the solubility of both statins can be considerably increased by the CD derivatives. The influence of the chemical structure of CD and of the temperature and pH on the solubility of the statin derivatives is described. Possible ways of increasing the solubility of these cholesterol-lowering drugs and their utilization in practice are also outlined.
Terrorism and Brain Drain in Pakistan: Is There a Connection?

This study empirically investigates the effect of terrorism and other push and pull factors on the skilled labour out-migration in Pakistan over the time period 1973–2015. The empirical findings based on fully modified ordinary least squares (FM-OLS) technique suggest that the waves of terrorism have not significantly driven the out-migration of skilled labour from Pakistan. Relatively, traditional push factors including inflation, unemployment and rising capital share in gross domestic product (GDP) have remained the major factors behind brain drain from Pakistan. Comparatively, the per capita economic growth, poverty and host and origin country’s emigration policies have curtailed the skilled out-migration. The findings suggest improving socio-economic conditions, increasing GDP per capita and decreasing unemployment and inflation in order to control the out-migration of skilled workers from Pakistan. Besides, the domestic labour market is required to boost the absorption capacity of highly educated and qualified workers in the country by making them more compatible to the existing stock of capital to restrict the brain drain. JEL: F22, F52, J24, C32