Miracle-dz/UniFAR-FTUs huggingface dataset:
Intracortical microstimulation pulse waveform and frequency recruits distinct spatiotemporal patterns of cortical neuron and neuropil activation

Objective. Neural prosthetics often use intracortical microstimulation (ICMS) for sensory restoration. To restore natural and functional feedback, we must first understand how stimulation parameters influence the recruitment of neural populations. ICMS waveform asymmetry modulates the spatial activation of neurons around an electrode at 10 Hz; however, it is unclear how asymmetry may differentially modulate population activity at frequencies typically employed in the clinic (e.g. 100 Hz). We hypothesized that stimulation waveform asymmetry would differentially modulate preferential activation of certain neural populations, and the differential population activity would be frequency-dependent. Approach. We quantified how asymmetric stimulation waveforms delivered at 10 or 100 Hz for 30 s modulated spatiotemporal activity of cortical layer II/III pyramidal neurons using in vivo two-photon and mesoscale calcium imaging in anesthetized mice. Asymmetry is defined in terms of the ratio of the duration of the leading phase to the duration of the return phase of charge-balanced cathodal- and anodal-first waveforms (i.e. longer leading phase relative to return has larger asymmetry). Main results. Neurons within 40–60 µm of the electrode display stable stimulation-induced activity indicative of direct activation, which was independent of waveform asymmetry. The stability of 72% of activated neurons and the preferential activation of 20%–90% of neurons depended on waveform asymmetry. Additionally, this asymmetry-dependent activation of different neural populations was associated with differential progression of population activity. Specifically, neural activity tended to increase over time during 10 Hz stimulation for some waveforms, whereas activity remained at the same level throughout stimulation for other waveforms. During 100 Hz stimulation, neural activity decreased over time for all waveforms, but decreased more for the waveforms that resulted in increasing neural activity during 10 Hz stimulation. Significance. These data demonstrate that at frequencies commonly used for sensory restoration, stimulation waveform alters the pattern of activation of different but overlapping populations of excitatory neurons. The impact of these waveform specific responses on the activation of different subtypes of neurons as well as sensory perception merits further investigation.
PHYSICS-BASED MODELING AND CONTROL OF POWERTRAIN SYSTEMS INTEGRATED WITH LOW TEMPERATURE COMBUSTION ENGINES

Low Temperature Combustion (LTC) holds promise for high thermal efficiency and low Nitrogen Oxides (NOx) and Particulate Matter (PM) exhaust emissions. Fast and robust control of different engine variables is a major challenge for real-time model-based control of LTC. This thesis concentrates on control of powertrain systems that are integrated with a specific type of LTC engines called Homogenous Charge Compression Ignition (HCCI). In this thesis, accurate mean value and dynamic cycleto-cycle Control Oriented Models (COMs) are developed to capture the dynamics of HCCI engine operation. The COMs are experimentally validated for a wide range of HCCI steady-state and transient operating conditions. The developed COMs can predict engine variables including combustion phasing, engine load and exhaust gas temperature with low computational requirements for multi-input multi-output realtime HCCI controller design. Different types of model-based controllers are then developed and implemented on a detailed experimentally validated physical HCCI engine model. Control of engine output and tailpipe emissions are conducted using two methodologies: i) an optimal algorithm based on a novel engine performance index to minimize engine-out emissions and exhaust aftertreatment efficiency, and ii) grey-box modeling technique in combination with optimization methods to minimize engine emissions. In addition, grey-box models are experimentally validated and their prediction accuracy is compared with that from black-box only or clear-box xlvii only models. A detailed powertrain model is developed for a parallel Hybrid Electric Vehicle (HEV) integrated with an HCCI engine. The HEV model includes sub-models for different HEV components. The HCCI map model is obtained based on extensive experimental engine dynamometer testing. The LTC-HEV model is used to investigate the potential fuel consumption benefits archived by combining two technologies including LTC and electrification. An optimal control strategy including Model Predictive Control (MPC) is used for energy management control in the studied parallel LTC-HEV. The developed HEV model is then modified by replacing a detailed dynamic engine model and a dynamic clutch model to investigate effects of powertrain dynamics on the HEV energy consumption. The dynamics include engine fuel flow dynamics, engine air flow dynamics, engine rotational dynamics, and clutch dynamics. An enhanced MPC strategy for HEV torque split control is developed by incorporating the effects of the studied engine dynamics to save more energy compared to the commonly used map-based control strategies where the effects of powertrain dynamics are ignored. LTC is promising for reduction in fuel consumption and emission production however sophisticated multi variable engine controllers are required to realize application of LTC engines. This thesis centers on development of model-based controllers for powertrain systems with LTC engines.
C-V2X Centralized Resource Allocation with Spectrum Re-Partitioning in Highway Scenario

Cellular Vehicle-to-Everything communication is an important scenario of 5G technologies. Modes 3 and 4 of the wireless systems introduced in Release 14 of 3GPP standards are intended to support vehicular communication with and without cellular infrastructure. In the case of Mode 3, dynamic resource selection and semi-persistent resource scheduling algorithms result in a signalling cost problem between vehicles and infrastructure, therefore, we propose a means to decrease it. This paper employs Re-selection Counter in centralized resource allocation as a decremental counter of new resource requests. Furthermore, two new spectrum re-partitioning and frequency reuse techniques in Roadside Units (RSUs) are considered to avoid resource collisions and diminish high interference impact via increasing the frequency reuse distance. The two techniques, full and partial frequency reuse, partition the bandwidth into two sub-bands. Two adjacent RSUs apply these sub-bands with the Full Frequency Reuse (FFR) technique. In the Partial Frequency Reuse (PFR) technique, the sub-bands are further re-partitioned among vehicles located in the central and edge parts of the RSU coverage. The sub-bands assignment in the nearest RSUs using the same sub-bands is inverted concerning the current RSU to increase the frequency reuse distance. The PFR technique shows promising results compared with the FFR technique. Both techniques are compared with the single band system for different vehicle densities.
AN ENERGY-BASED DAMAGE DETECTION ALGORITHM BASED ON MODAL DATA

In recent years, significant efforts have been devoted to developing non-destructive techniques for damage identification in structures. Damage detection techniques based on modal testing rely on the fact that the occurrence of damage or loss of integrity in a structural system leads to changes in the dynamic properties of the structure. In this paper, an energy index based on mode shapes and their derivative is applied to detect damage in reinforced concrete beams isintroduced. The effectiveness of the proposed methods is examined through analytical model on an RC beam. Results illustrate that the energy index is sensitive to damage, and the proposed method is simple and robust in locating single or multiple damages in a structure. INTRODUCTION Many civil engineering structures, exposed to various external loads such as earthquakes, traffic and wind during their lifetime, have been suffering damage and deterioration in recent years which seriously affects their performance and may even lead to structural failure. The same phenomena are applicable in aerospace and mechanical engineering. Because of this, structural health monitoring and damage assessment of these structures is becoming increasingly important in order to determine their safety and reliability. Nondestructive inspection techniques, such as ultrasonic and acoustic emission methods, X-ray methods, etc., are generally used to investigate the critical changes experienced by the structural parameters with the purpose of preventing unexpected structural failures. These kinds of experimental techniques are based on a local evaluation ineasily accessible areas and, therefore, they require a certain a priori knowledge of the damage distribution. Furthermore, they are costly and, in order to perform an inspection, the structure needs to be taken out of service. However, nowadays, techniques based on modal testing(Ewins, 1984) and signal processing constitute a promising nondestructive tool for damage identification in many engineering applications, including civil engineering applications. Using these techniques modal parameters (frequencies, mode shapes and damping ratios) can be extracted easily and cheaply from measurements of vibration-based dynamic tests. Changes in the modal parameters of a structure imply changes in its mass, damping and/or stiffness properties and, therefore, serve as a basis not only for finite-element modal updating (Ren et al., 2004) but also for structural damage detection (Casas and Aparicio, 1994), (Doebling et al., 1998). The comparison between the undamaged and damaged structure makes possible the identification of the location and the severity of
Isolation, Identification and Evaluation of Indigenous Plant Growth Promoting Bacterium Klebsiella pneumoniae PNE1

Application of chemical fertilizer is an integral practice to optimize crop productivity, but the dominant use of chemical fertilizers contributes largely to the deterioration of the environment, leads to loss of soil fertility, increases pollution, and causes hazardous diseases. Hence, the chemical fertilizers, pesticides and other supplements are being replaced by the plant growth promoting bacteria (PGPB) due to their improved potency and environment friendly nature. Plant growth-promoting bacteria (PGPB) can enhance plant growth by a wide variety of mechanisms like Phosphate (P) solubilization, Potassium solubilisation, siderophore production, biological nitrogen fixation and Indole acetic acid (IAA) production. The Klebsiella species is also known to exhibit important PGP traits like solubilization of phosphate, phytohormone production and good germination potential. In present study the Klebsiella pneumoniae PNE1 was selected from the isolates obtained from vegetable waste collected from Kadi market. The isolate was selected on the basis of its ability for Nitogen fixation, Phosphate solubilization, Potassium solubilization, IAA production, EPS production and biopolymer degradation. The molecular identification through 16S rRNA gene sequence, confirmed the isolate as Klebsiella pneumonia PNE1. Quantitative analysis of ammonia production revealed that isolate Klebsiella pneumonia PNE1 produced 0.5 µg/ml of ammonia (NH3) on 6th day of incubation and produced 0.09 µg/ml Nitrite after 8th day of incubation. The Phosphate solubilisation Index (SI) of the isolate was 4.16 and the isolate released 177.50 μg/ml Phosphate. The qualitative estimation of Potassium solubilisation by the isolate Klebsiella pneumoniae PNE1 in terms of Potassium solubilisation zone was found to increase gradually from day 1 to 7 days and was maximum at 2nd day with a KSI of 3.6. The isolate Klebsiella pneumoniae PNE1 released 29.94 mg/l Potassium on 21th day of incubation respectively. The IAA production was found to be 94.96 µg/ml. The maximum the EPS yield was 11.3 mg/ml. The Klebsiella pneumonia PNE1 had capacity to degrade Cellulose, Pectin and Xylan i.e. all biopolymers tested. The antibiotic susceptibility test indicated that isolate was sensitive to all 22 antibiotics tested. The Klebsiella pneumonia PNE1 thus, shows important plant growth promoting traits and can be used in a bio-fertilizer formulation for sustainable agriculture.
Exploring the Critical Thinking Process of Prospective Teachers with High Mathematics Ability in Solving Ill-Structured Problems

This study explored the features of critical thinking process skills of prospective teachers with high mathematics abilities in the process of solving ill-structured problems in mathematics classes of private universities in Makassar, Indonesia. Participants solved ill-structured problems by following the analyze, browse, create, decision-making, and evaluate stages. Thirty teacher candidates were selected to complete a math proficiency test. Prospective teachers were grouped based on high mathematical ability. Then they were interviewed based on the results of the Ill-Structured problem-solving. Based on the analysis and discussion, the results showed that the subjects could carry out critical thinking processes in solving ill-structured problems through five (5) stages/phases as follows. Analyze; Subjects could understand the problem by identifying the information needed and defining the problem given. Browse Subjects had the ability to mention or write by grouping relevant information to solve the given problem. Create; Subjects were able to formulate and create alternative problem-solving in written form accompanied by reasoning. Decision-making; The subjects were able to solve the problem by connecting the information obtained to find a common thread of a problem so that the end can be described from a tangled condition. Evaluate; The subjects were able to evaluate the steps to solving the problem and obtain the results or answers in accordance with the target they wanted to achieve. This study’s findings suggest that this process can be used to help detect the thought process features of teacher candidates for solving Ill-Structured problems in mathematics education and for future research.
Carbetocin versus oxytocin for the prevention of postpartum hemorrhage after elective caesarean section in high risk women: a prospective, randomized, open-label, controlled trial in China

Background: To evaluate the efficacy and safety of carbetocin compared with oxytocin for prevention of postpartum hemorrhage (PPH) after elective cesarean section in Chinese high risk women. Methods: This was a single-center, prospective, randomized, open-label, controlled trial recruiting 852 pregnant women with one or more PPH risk factors between April 2017 and August 2019. Pregnant woman who was scheduled for an elective cesarean section were randomly assigned to receive carbetocin or oxytocin for prevention of PPH. The primary efficacy endpoint was the proportion of additional uterotonics. Results: A total of 852 pregnant women were randomly assigned to receive carbetocin (n = 442) or oxytocin (n = 410). The baseline characteristics were comparable between the two groups. The carbetocin group had lower proportion of requiring additional uterotonics (18.4% vs. 24.4%, p = 0.03 in full analysis set [FAS] analysis) to the oxytocin group. The amount of blood loss (intrapartum or postpartum) was no statistically significant difference (all p > 0.05). There were no significant differences in the postpartum hemoglobin, rate of hemostatics, blood transfusion, additional surgical interventions or uterine massage between the two groups. The rates of mild asphyxia in carbetocin and oxytocin groups were 2.1% and 1.3%, respectively. No other poor maternal and neonatal outcomes were observed in two groups. Conclusions: Carbetocin required lower rate of additional uterotonics than oxytocin for prevention of PPH after elective cesarean section in Chinese high risk women. Carbetocin was comparable to oxytocin in postpartum blood loss, postpartum hemoglobin, hemostatics, blood transfusion, additional surgical interventions or uterine massage.
Genetic diversity of Coffea canephora Pierre ex A. Froehner in Temanggung District, Indonesia based on molecular marker RAPD

Authors. 2021. Genetic diversity of Coffea canephora Pierre ex A. Froehner in Temanggung District, Indonesia based on molecular marker RAPD. Biodiversitas 22: 4775-4783. Temanggung District in Central Java Province, Indonesia is one of robusta coffee production centers. The condition of coffee plantations in Temanggung shows variations in some morphological traits. Variations in coffee phenotypes are considered less profitable for farmers because they produce yields of undesirable quality in the global market. This study aimed to evaluate the genetic diversity of robusta coffee in Temanggung. The coffee plants were derived from six villages located at two levels of altitude. The morphological traits were observed from canopy width, trunk diameter, plant height, cherry volume, and bean volume, while the biochemical compositions were determined by caffeine content and brew’s pH value. The molecular assays were performed using PCR-RAPD with ten primers and species identification was based on the ITS rDNA. Our finding showed a variation in all morphological characters and biochemical compositions based on the LSD test 5%. The molecular marker RAPD revealed the genetic diversity by showing the DNA polymorphism levels of 95%, with the genetic similarity coefficient ranged from 0.35 to 0.86. The species identification also demonstrated that our robusta coffee was 97.11-99.70% similar to robusta coffee MK615737.1 from Philippines and robusta coffee DQ153593.1 from Cameroon. Thus, genetic diversity on six populations of robusta coffee was found, along with its variations on phenotypes which might lead the coffee yield quality to become uneven.
A REVIEW ON STIMULATING MODELS OF RAILWAYS

In the past years Rail vehicle modelling and stimulations have developed a long way from its origin. This paper presents a brief study on modern stimulating models of railways, their applications and what all challenges we are facing currently in this field. The both linear, non-linear models have been discussed in this study. Finite Element geometric model of the bogie and railway coach have also been studied in this paper. Critical aspects related with programming approach, computational demand in simulation of railway vehicle problems have been discussed. Important aspects related with traction drives, traction power supply and drive system, modified load flow approach, direct matrix method, static and dynamic ordering have also been critically discussed in this paper. Further this paper discusses varies aspects and criteria’s that are required to be considered while characterizing stimulating models in railways and what all developments are happening or will happen in near future in this field. Here different methods and approaches regarding optimum performance of suspension, wheel-rail contact and modelling inputs such as track geometry etc have also been discussed. The Finite element modeling of railway vehicle enables the researchers to incorporate the flexibility in the different parts of the railway vehicle system. Linear and non-linear rigid body modeling provides the researchers to examine each component of the railway vehicle system individually.
OP-HURU210030 1..15

and title screening n = 26,250 (+2,765)* Records excluded: n = 20,626 1. Paper not in English: 2,654 2. Study not in humans: 5,060 3. Study topic irrelevant:12,912 Full text screening: n = 5,624 (+534)* Records excluded: n = 4,141 4. Association study: 745 5. AZF deletion: 505 6. Multiple genes affected: 36 7. Karyotype anomaly: 1,209 8. Irrelevant: 981 9. Full text unavailable: 42 Records identified from: Reviews and reference lists n = 43
Designing tsunami risk communication with communities: A site-specific case study from Tūranganui-a-Kiwa, Aotearoa New Zealand

This paper describes a student research project that proposes ways to build earthquake and tsunami awareness through a community-centred approach to tell the story of tsunami as a potential risk. This project is centred on Tūranganui-a-Kiwa (the Poverty Bay region on the East Coast of Aotearoa New Zealand’s North Island), an area close to the Hikurangi Subduction Zone which is liable to produce tsunami with little or no time for an official warning. Recent research has revealed that these coastal communities have low levels of tsunami awareness and high expectations of receiving a formal warning before evacuation. In response, this project examined ways to incorporate Mātauranga Māori with Human-Centred Design to produce a meaningful and relevant narrative for encouraging community conversations about tsunami risk. This approach can increase ownership of risk management and recognises that communities, especially tangata whenua “people of the land”, or indigenous communities who have authority in a particular place hold various bodies of knowledge that can contribute to future risk management. A combination of methods comprised a co-design process, underpinned by Kaupapa Māori research principles, including developing personas and conducting semi-structured interviews and participatory workshops. A narrative developed through this design process manifested in a sculptural pouwhenua marker posts, usually carved, that are used to mark boundaries of significant places articulating local earthquake and tsunami hazards. This speculative output was presented in Wellington and Tūranganui-a-Kiwa and is envisaged as an ongoing conversation prompt. This paper describes and reflects on this research process as one that intertwined Human-Centred Design with the author's own situated knowledge as an emerging Māori design researcher. It suggests that a design process that is responsive to community, geography, and culture, undertaken without a predetermined outcome, is valuable in two ways: for the learning that takes place dialogically through the process itself and the potential for an artefact initiated through this process, which embeds narrative storytelling, to catalyse further dialogue in the community and expert groups and between the two.
Evaluation of Wave-induced Liquefaction in a Porous Seabed: Using an Artificial Neural Network and a Genetic Algorithm -based model

The evaluation of wave-induced liquefaction is one of the key factors for analysing seabed characteristics and the design of marine structures. Numerous investigations of wave-induced liquefaction have been proposed. However, most previous research has focused on complicated mathematical theories and laboratory work. In this study, we contribute an alternative approach for the prediction of the waveinduced liquefaction using an Artificial Neural Network (ANN) and a Genetic Algorithm (GA)-based model. Combined ANN and GA-based models are still a newly developed area in coastal engineering. In this study, a Genetic Algorithm-based approach is proposed to find optimal weights for the ANN model. It reduces the training time, and improves the forecasting accuracy for wave-induced maximum liquefaction depth, compared to using the normal ANN training procedure. Simulation results demonstrate the capacity of the proposed ANN model for the prediction of wave induced maximum liquefaction depth in addition to the proposal of GAs for training the ANN model.