Miracle-dz/UniFAR-FTUs huggingface dataset:
Posiphen Reduces the Levels of Huntingtin Protein through Translation Suppression

Posiphen tartrate (Posiphen) is an orally available small molecule that targets a conserved regulatory element in the mRNAs of amyloid precursor protein (APP) and α-synuclein (αSYN) and inhibits their translation. APP and αSYN can cause neurodegeneration when their aggregates induce neurotoxicity. Therefore, Posiphen is a promising drug candidate for neurodegenerative diseases, including Alzheimer’s disease and Parkinson’s disease. Posiphen’s safety has been demonstrated in three independent phase I clinical trials. Moreover, in a proof of concept study, Posiphen lowered neurotoxic proteins and inflammatory markers in cerebrospinal fluid of mild cognitive impaired patients. Herein we investigated whether Posiphen reduced the expression of other proteins, as assessed by stable isotope labeling with amino acids in cell culture (SILAC) followed by mass spectrometry (MS)-based proteomics. Neuroblastoma SH-SY5Y cells, an in vitro model of neuronal function, were used for the SILAC protein profiling response. Proteins whose expression was altered by Posiphen treatment were characterized for biological functions, pathways and networks analysis. The most significantly affected pathway was the Huntington’s disease signaling pathway, which, along with huntingtin (HTT) protein, was down-regulated by Posiphen in the SH-SY5Y cells. The downregulation of HTT protein by Posiphen was confirmed by quantitative Western blotting and immunofluorescence. Unchanged mRNA levels of HTT and a comparable decay rate of HTT proteins after Posiphen treatment supported the coclusion that Posiphen reduced HTT via downregulation of the translation of HTT mRNA. Meanwhile, the downregulation of APP and αSYN proteins by Posiphen was also confirmed. The mRNAs encoding HTT, APP and αSYN contain an atypical iron response element (IRE) in their 5′-untranslated regions (5′-UTRs) that bind iron regulatory protein 1 (IRP1), and Posiphen specifically bound this complex. Conversely, Posiphen did not bind the IRP1/IRE complex of mRNAs with canonical IREs, and the translation of these mRNAs was not affected by Posiphen. Taken together, Posiphen shows high affinity binding to the IRE/IRP1 complex of mRNAs with an atypical IRE stem loop, inducing their translation suppression, including the mRNAs of neurotoxic proteins APP, αSYN and HTT.
Quantification of Heavy Metals and Pesticide Residues in Widely Consumed Nigerian Food Crops Using Atomic Absorption Spectroscopy (AAS) and Gas Chromatography (GC)

More still needs to be learned regards the relative contamination of heavy metals and pesticide residues, particularly those found in widely consumed Nigerian food crops like cereals, vegetables, and tubers. In this current study, the heavy metals and pesticide residues detectable in widely consumed Nigerian food crops were respectively quantified using atomic absorption spectroscopy (AAS) and gas chromatography (GC). Specifically, the widely consumed Nigerian food crops included cereals (rice, millet, and maize), legume (soybean), tubers (yam and cassava), as well as leaf (fluted pumpkin, Amaranthus leaf, waterleaf, and scent leaf) and fruit vegetables (okro, cucumber, carrot, and watermelon). Results showed that the detected heavy metals included arsenic (As), cadmium (Cd), chromium (Cr), cobalt (Co), iron (Fe), lead (Pb), manganese (Mn), mercury (Hg), and nickel (Ni), whereas the pesticide residues included Aldrin, Carbofuran, g-chlordane, Chlorpyrifos, DichloroBiphenyl, Dichlorodiphenyldichloroethane (DDD), Dichlorodiphenyltrichloroethane (DDT), Dichlorvos, Endosulfan, Heptachlor, Hexachlorobenzene (HCB), Isopropylamine, Lindane, t-nonachlor, and Profenofos. Across the studied food crops, the concentrations of heavy metals and pesticides were varied, with different trends as they largely fell below the established maximum permissible limits, and with some exceptions. Our findings suggest there could be a somewhat gradual decline in the concentration of the heavy metals and pesticide residues of these studied food crops when compared to previously published reports specific to Nigeria. To help substantiate this observation and supplement existing information, further investigations are required into the concentration of these heavy metals and pesticide residues specific to these studied food crops at other parts of the country.
Lot-sizing under uncertainty in a rolling schedule environment

SUMMARY This paper presents results from a simulation experiment evaluating 14 different single stage lot-sizing procedures. Uncertainty in the form of forecast errors was used as one factor in the experiment. In order to prevent different service levels from confounding cost comparisons, enough safety stock to achieve a 100% service level in all situations was introduced. The ranking of the rules under uncertainty turned out to be very different from the ranking when no demand uncertainty was present. Statistical differences were found between the six best lot-sizing procedures when there was no uncertainty. When forecast errors were present, however, no differences existed for the six best rules in this situation. Thus, uncertainty not only changed the relationship between the lot-sizing rules, but also the character of this relationship.
Fire in lichen-rich subarctic tundra changes carbon and nitrogen cycling between ecosystem compartments but has minor effects on stocks

Abstract. Fires are predicted to increase in Arctic regions due to ongoing climate change. Tundra fires can alter carbon and nutrient cycling and release a substantial amount of greenhouse gases with global consequences. Yet, the long-term effects of tundra fires on carbon (C) and nitrogen (N) stocks and cycling are still unclear. Here we used a space-for-time approach to investigate the long-term fire effects on C and N stocks and cycling in soil and aboveground living biomass. We collected data from three large fire scars (> 44, 28 and 12 years old) and corresponding control areas and used linear mixed-effects models in a Bayesian framework to analyse how the stocks and cycling were influenced by fire. We found that tundra fires did not affect total C and N stocks because a major part of the stocks was located belowground in soils, which were largely unaltered by fire. However, fire had a strong effect on stocks in the aboveground vegetation, mainly due to the reduction of the lichen layer. Fire reduced N concentrations in graminoids and herbs on the younger fire scars, which affected respective C / N ratios and indicated an increased post-fire competition between vascular plants. Aboveground plant biomass was depleted in 13C in all three fire scars. This could be related to a lower 13C abundance in CO2 in the ambient air because of increased post-fire decomposition, providing a source of 13C-depleted CO2. In soil, the relative abundance of 13C changed with time after fire because of the combined effects of microbial decomposition and plant-related fractionation processes. Our results indicate that in lichen-rich subarctic tundra ecosystems, the contribution of fires to the release of additional carbon to the atmosphere might be relatively small as soil stocks appear to be resilient.
Research on Electromagnetic and Dynamic Properties of LPMBLDCM for Electromagnetic Launch

In order to improve the thrust characteristics of moving-magnet type linear permanent magnet brushless DC motor (LPMBLDCM), the structural characteristics and magnetic field are analyzed. The influence of electrical parameters and structural parameters on the electromagnetic properties and thrust performance are researched by finite element analysis (FEA). The cogging force, back electromotive force (back-EMF), air-gap magnetic field distribution, mover velocity as well as thrust output are studied by taking some practical parameters into account, including pole/arc coefficient, air-gap width, voltage and current. The LPMBLDCM system is established, and some relevant tests are taken to verify the simulation results. Simulation and experimental results show that the thrust and mover velocity are mainly affected by some key parameters. The results will surely provide the reference and guidance for the optimization of electromagnetic and thrust characteristics of LPMBLDCM.
A Comparison of Survival after Radiosurgery in Non-Small Cell  Lung Cancer  Patients with One versus More than Twenty Brain Metastases

Background Whether the number or cumulative volume of brain metastases affects survival in patients with metastatic non-small cell lung cancer (NSCLC) remains controversial. We sought to compare whether patients with solitary brain disease had better outcomes than patients with ≥ 20 brain metastases. Methods Between 2014 to 2020, 26 NSCLC patients (925 tumors) underwent stereotactic radiosurgery (SRS) for ≥ 20 metastases in a single procedure (median margin dose = 16 Gy, median cumulative tumor volume = 4.52 cc); 56 patients underwent SRS for a single metastasis (median margin dose = 18 Gy, median volume = 4.74 cc). The overall survival (OS), local tumor control (LC), adverse radiation effect (ARE) risk, and incidence of new tumor development were compared. Results No difference in OS was found between patients with ≥ 20 brain metastases (median OS = 15 months) and patients with solitary metastasis (median OS = 12 months; p = 0.3). In the solitary tumor cohort, two of 56 (3.5%) tumors progressed whereas in the ≥ 20 cohort only 3 of 925 (0.3%) tumors showed progression (*p = 0.0013). The rate of new tumor development was significantly higher in patients with ≥ 20 tumors (***p = 0.0001). No significant difference of ARE rate was found (7.5% for ≥ 20 tumors vs. 8.7% for single metastasis). Conclusions Patients with ≥ 20 tumors showed significantly better LC with similar OS compared to patients with solitary tumors. Current guidelines that restrict the role of SRS to patients with 1-4 tumors should be revised.
Evaluating Alternatives to Locomotion Scoring for Lameness Detection in Pasture-Based Dairy Cows in New Zealand: Infra-Red Thermography

Simple Summary Early detection accompanied by effective treatment is vital to minimise the negative impacts of lameness in dairy cows. Locomotion scoring is commonly used for detecting lameness but can be challenging to implement effectively in cows at pasture-based systems. One potential alternative detection is measuring foot skin temperature using an infrared camera. Data were collected from a 940-cow dairy farm in New Zealand with cows observed at two consecutive afternoon milkings. Locomotion scoring was undertaken at the first milking and thermal imaging of the hind feet at the second milking. As the locomotion score increased, mean foot skin temperature increased, showing that measuring temperature could be a useful alternative to locomotion scoring. However, the process needs to be speeded up and automated if it is to be used widely. Abstract Lameness in cattle is a complex condition with huge impacts on welfare, and its detection is challenging for the dairy industry. The present study aimed to evaluate the association between foot skin temperature (FST) measured using infrared thermography (IRT) and locomotion scoring (LS) in dairy cattle kept at pasture. Data were collected from a 940-cow dairy farm in New Zealand. Cows were observed at two consecutive afternoon milkings where LS was undertaken at the first milking (4-point scale (0–3), DairyNZ). The next day, cows were thermally imaged from the plantar aspect of the hind feet using a handheld T650sc forward-looking infrared camera (IRT). The association between FST and locomotion score was analysed using a generalised linear model with an identity link function and robust estimators. ROC curves were performed to determine optimal threshold temperature cut-off values by maximising sensitivity and specificity for detecting locomotion score ≥ 2. There was a linear association between individual locomotion scores and FST. For mean temperature (MT), each one-unit locomotion score increase was associated with a 0.944 °C rise in MT. Using MT at a cut-off point of 34.5 °C produced a sensitivity of 80.0% and a specificity of 92.4% for identifying cows with a locomotion score ≥ 2 (lame). Thus, IRT has a substantial potential to be used on-farm for lameness detection. However, automation of the process will likely be necessary for IRT to be used without interfering with farm operations.
Computer Synthesized Speech Technologies: Tools for Aiding Impairment

Computer Synthesized Speech Technologies: Tools for Aiding Impairment provides information to current and future practitioners that will allow them to better assist speech disabled individuals who wish to utilize CSS technology. Just as important as the practitioner's knowledge of the latest advances in speech technology, so, too, is the practitioner's understanding of how specific client needs affect the use of CSS, how cognitive factors related to comprehension of CSS affect its use, and how social factors related to perceptions of the CSS user affect their interaction with others. This cutting edge book addresses those topics pertinent to understanding the myriad of concerns involved with the implementation of CSS so that CSS technologies may continue to evolve and improve for speech impaired individuals.
Low intermodulation class-F power amplifier

In this paper the design of a low IM and efficient class-F power amplifier in the L-band is presented. To improve intermodulation and efficiency, termination of the generated 2nd harmonic frequency at the input was investigated and optimized. For optimum termination of the harmonics at the device's input and output a scaleable inductor model to realize inductors with high Q-factors and tight tolerances was developed. Based on DC and small-signal parameter characterization a nonlinear computer model was fitted. To minimize, the amplifier was realized in this film technology. Simulation results are compared to measurement results and show good agreement.
Measurement Plans for Process Flow Improvement in Services and Health Care

ABSTRACT The discussion of performance measurement is often on a conceptual, not operational, level; advice on the operational and practical matters of obtaining data for process flow improvement is scarce. We define a measurement plan and study four measurement study designs and corresponding methods and techniques, illustrating these with practical applications and solutions. The measurement plan is presented as a tool to organize the measurement systems for process flow improvement in services and health care. Our study contributes terminology to the methodological development of improvement initiatives, and we present a tool for practitioners to organize the measurements in process flow improvement projects.
V2O5/NaV6O15 nanocomposites synthesized by molten salt method as a high-performances cathode material for aqueous zinc-ion batteries

Aqueous zinc-ion batteries (ZIBs) is a potential energy storage system due to its advantages of low cost, good safety, and high theoretical capacity (820 mAh g−1). However, the lack of cathode materials with long cycle stability severely restricts the development of ZIBs. In this paper, V2O5/ NaV6O15 nanocomposites are synthesized by molten salt method in one step and used as cathode material for ZIBs, which have good electrochemical performances. The specific capacity of the materials remain 160 mAh g−1 when the current density is 0.5 A g−1 after 1000 cycles, and the capacity retention rate is 102.03% when the current density is 5 A g−1 for 1000 cycles. This is mainly due to the large number of active sites generated by crystal defects and the synergistic interaction between the dual-phase materials, which reduces the stress of ions inserted/extracted during the Zn2+ storage process and improves the electrochemical performance.
Quality Control and Discrimination of Andrographis paniculata (Burm. f.) Nees based on High Performance Liquid Chromatography Fingerprinting Combined with Chemometric Approaches

Andrographis paniculata (Burm. f.) Nees is a potential medicinal herb used to treat a wide range of diseases. Various geographical origins of this herb might lead to the diversity of the herbal quality. The research aims to establish the chemical fingerprint for quality control of Andrographis paniculata and to find out the chemical markers for discrimination from different origin through the chemometrics approach. A high performance liquid chromatography photo diode array method was developed for simultaneous quantification of five marker compounds and for establishing the chemical fingerprint of Andrographis paniculata from 28 different locations of Eastern India. Chemometrics techniques including hierarchical cluster analysis, principal component analysis and partial least squares discriminant analysis were used. The similarities between each fingerprint of the sample and the simulative mean chromatogram were greater than 0.90. The relative standard deviation of relative retention time and relative peak area of precision, stability and repeatability of 12 characteristic peaks in these samples were less than 1 % and 3 %, respectively. The andrographolide content in the Odisha region varied in the range of 2.68-5.47 %. The results of hierarchical cluster analysis, principal component analysis and partial least squares discriminant analysis showed that Andrographis paniculata could be successfully grouped into two groups in accordance with the origin. Andrographolide (variable importance in projection score >1.5) was the key discriminatory marker for discriminating the samples. The high performance liquid chromatography fingerprint combined with chemometric approaches could be used as an effective tool for discriminating the herb from different origins and quality control of Andrographis paniculata.
Evaluation of Active Layer Thickness Influence in Long-Term Stability and Degradation Mechanisms in CsFAPbIBr Perovskite Solar Cells

Perovskite solar cells (PSCs) have become very popular due to the high efficiencies achieved. Nevertheless, one of the main challenges for their commercialization is to solve their instability issues. A thorough understanding of the processes taking place in the device is key for the development of this technology. Herein, J-V measurements have been performed to characterize PSCs with different active layer thicknesses. The solar cells’ parameters in pristine devices show no significant dependence on the active layer thickness. However, the evolution of the solar cells’ efficiency under ISOS-L1 protocol reveals a dramatic burn-in degradation, more pronounced for thicker devices. Samples were also characterized using impedance spectroscopy (IS) at different degradation stages, and data were fitted to a three RC/RCPE circuit. The low frequency capacitance in the thickest samples suffers a strong increase with time, which suggests a significant growth in the mobile ion population. This increase in the ion density partially screens the electric field, which yields a reduction in the extracted current and, consequently, the efficiency. This paper has been validated with two-dimensional numerical simulations that corroborate (i) the decrease in the internal electric field in dark conditions in 650 nm devices, and (ii) the consequent reduction in the carrier drift and, therefore, of the effective current extraction and efficiency.
A 22 GHz cascode CMOS VCO using frequency doubler

This paper presents a fully integrated cascode CMOS LC VCO using frequency doubler for oscillating at 22 GHz band. A symmetrical cascode coupling topology is implemented with negative conductance scheme for increasing the quality factor and output swing. Therefore, this architecture improves the phase noise characteristic in 0.18 μm CMOS technology. In order to oscillate at 22 GHz band the frequency doubler (clipper) is used. The measured phase noise is −102.4 dBc/Hz at the 1 MHz offset frequency. The tuning range of 1.32 GHz is obtained with the control voltage from 0.5 to 1.6 V. The current consumption of the VCO and the frequency doubler has 11.8 mA from 1.8 V supply. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 49: 2870–2873, 2007; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.22857
Hyperspectral digital imagery collection experiment (HYDICE)

In order to advance the state-of-the-art in the collection of imaging spectroscopy, the U.S. Navy Space and Warfare Systems Command sponsored the development and fabrication of a new generation, well calibrated hyperspectral imaging spectrometer. Called the Hyperspectral Digital Imagery Collection Experiment (HYDICE), the sensor was built by Hughes Danbury Optical Systems, Danbury, Conn. , delivered for integration into the Environmental Institute of Michigan's (ERIM) CV-580 aircraft in December 1994, tested and characterized between January and June 1995, and has since been involved in several airborne data collection experiments. In this paper, the HYDICE Program Office organization, sensor specifications, airborne characterization results, and a summary of the results of the most recent data exploitation and analyses are presented.
for Log

— Automated machine learning and predictive maintenance have both become prominent terms in recent years. Combining these two fields of research by conducting log analysis using automated machine learning techniques to fuel predictive maintenance algorithms holds multiple advantages, especially when applied in a production line setting. This approach can be used for multiple applications in the industry, e.g., in semiconductor, automotive, metal, and many other industrial applications to improve the maintenance and production costs and quality. In this paper, we investigate the possibility to create a predictive maintenance framework using only easily available log data based on a neural network framework for predictive maintenance tasks. We outline the advantages of the ALFA (AutoML for Log File Analysis) approach, which are high efficiency in combination with a low entry border for novices, among others. In a production line setting, one would also be able to cope with concept drift and even with data of a new quality in a gradual manner. In the presented production line context, we also show the superior performance of multiple neural networks over a comprehensive neural network in practice. The proposed software architecture allows not only for the automated adaption to concept drift and even data of new quality but also gives access to the current performance of the used neural networks.
Condition monitoring of vibrating steel‐reinforced concrete beams through wavelet transforms

Purpose – The purpose of this research is to show that wavelets are mathematical tools capable of separating vibration data into different frequency components, allowing the study of each component with a resolution matched to its specific time scale. Wavelets have advantages over traditional Fourier methods, particularly when a signal contains sharp spikes, discontinuities, and transients.Design/methodology/approach – This paper presents a brief description of wavelets and shows their application to the analysis of typical transient signals due to vibrations in a steel‐reinforced concrete beam.Findings – The research clearly shows that it is possible to evaluate modes and components separately by using the wavelet analysis.Originality/value – The beam analysed can be used as a simple model of other more complicated structures, such as bridges and other high scale civil engineering constructions, where vibration analysis is a key issue for maintenance and failure assessments, thus representing an alternat.