Miracle-dz/UniFAR-FTUs huggingface dataset:
Enriched Environment Effects on Myelination of the Central Nervous System: Role of Glial Cells

Myelination is regulated by various glial cells in the central nervous system (CNS), including oligodendrocytes (OLs), microglia, and astrocytes. Myelination of the CNS requires the generation of functionally mature OLs from OPCs. OLs are the myelin-forming cells in the CNS. Microglia play both beneficial and detrimental roles during myelin damage and repair. Astrocyte is responsible for myelin formation and regeneration by direct interaction with oligodendrocyte lineage cells. These glial cells are influenced by experience-dependent activities such as environmental enrichment (EE). To date, there are few studies that have investigated the association between EE and glial cells. EE with a complex combination of sensorimotor, cognitive, and social stimulation has a significant effect on cognitive impairment and brain plasticity. Hence, one mechanism through EE improving cognitive function may rely on the mutual effect of EE and glial cells. The purpose of this paper is to review recent research into the efficacy of EE for myelination and glial cells at cellular and molecular levels and offers critical insights for future research directions of EE and the treatment of EE in cognitive impairment disease.
Why is adoption of micro-irrigation slow in India? a review

ABSTRACT Adoption of micro-irrigation has been slow among farmers in India in spite of concerted efforts. Based on a systematic literature review, this article makes two observations. First, subsidies alone will not lead to greater adoption since decisions on adoption are shaped by household, farm level and institutional factors. Secondly, mere adoption of micro-irrigation will not result in water conservation because farmers are seen to expand the area under irrigation or shift to water-intensive crops. The article argues for better recognition of the diverse contextual factors and interests of farmers in formulating effective mechanisms to ensure adoption and use of micro-irrigation.
Topographic controls on ice flow and recession for Juneau Icefield (Alaska/British Columbia)

Globally, mountain glaciers and ice caps are losing dramatic volumes of ice. The resultant sea‐level rise is dominated by contributions from Alaska. Plateau icefields may be especially sensitive to climate change due to the non‐linear controls their topography imparts on their response to climate change. However, Alaskan plateau icefields have been subject to little structural glaciological or regional geomorphological assessment, which makes the controls on their present and former mass balance difficult to ascertain.
Feature extractions and selection of bot detection on Twitter A systematic literature review: Feature extractions and selection of bot detection on Twitter A systematic literature review

Abstract Automated or semiautomated computer programs that imitate humans and/or human behavior in online social networks are known as social bots. Users can be attacked by social bots to achieve several hidden aims, such as spreading information or influencing targets. While researchers develop a variety of methods to detect social media bot accounts, attackers adapt their bots to avoid detection. This field necessitates ongoing growth, particularly in the areas of feature selection and extraction. The study's purpose is to provide an overview of bot attacks on Twitter, shedding light on issues in feature extraction and selection that have a significant impact on the accuracy of bot detection algorithms, and highlighting the weaknesses in training time and dimensionality reduction. To the best of our knowledge, this study is the first systematic literature review based on a preset search-strategy that encompasses literature published between 2018 and 2021 which are concerned with Twitter features (attributes). The key findings of this research are threefold. First, the paper provides an improved taxonomy of feature extraction and selection approaches. Second, it includes a comprehensive overview of approaches for detecting bots in the Twitter platform, particularly machine learning techniques. The percentage was calculated using the proposed taxonomy, with metadata, tweet text, and merging (meta and tweet text) accounting for 37%, 31%, and 32%, respectively. Third, some gaps are also highlighted for further research. The first is that public datasets are not precise or suitable in size. Second, the use of integrated systems and real-time detection is uncommon. Third, detecting each bots category identified separately is needed, rather than detecting all categories of bots using one generic model and the same features' values. Finally, extracting influential features that assist machine learning algorithms in detecting Twitter bots with high accuracy is critical, especially if the type of bot is pre-determined.
World Journal of Gastroenterology Development and validation of a prediction model for moderately severe and severe acute pancreatitis in pregnancy

The severity of acute pancreatitis A nomogram including lactate dehydrogenase, triglyceride, cholesterol, and albumin levels as independent predictors was built with good performance for MSIP prediction. Core Tip: The severity of acute pancreatitis in pregnancy (APIP) is correlated with higher risks of maternal and fetal death. Few studies have focused on APIP severity prediction. We identified four predictors developed and established a prediction nomogram model for pregnant patients with moderate and severe acute pancreatitis. This model achieved good concordance indexes and may help guide doctors in the managementof APIP. and validation of a prediction model for and predicted MSIP probability actual MSIP proportion. Values of perfect and no
An Electric-Hydrostatic Energy Storage System for Hydraulic Hybrid Wheel Loader

As a typical energy storage in hydraulic hybrid powertrain, the hydraulic accumulator has high power density but low energy density. There are some efforts in improving the energy density of hydraulic energy storage to achieve balanced performance. Therefore in this study an electric-hydrostatic energy storage system is proposed to replace hydraulic accumulator in a hydraulic hybrid wheel loader. Through active control of proposed energy storage, constant system pressure is possible to provide good vehicle drivability. A rule-based energy management strategy without estimating final drive power is proposed. The vehicle performance and fuel consumption with different constant system pressures are studied. Results show the vehicle fuel consumption is reduced by 5.9% with constant system pressure reduced from 33 to 27 MPa. The energy density and power density of proposed energy storage are calculated, showing a much higher energy density and slightly lower power density than gas-charged accumulator.
Insight into the Contact Impedance between the Electrode and the Skin Surface for Electrophysical Recordings

To obtain a performance improved dry electrode for bioelectrical activity detection is still a challenge, which is mainly due to the poor fundamental understanding on the impedance of the electrode–skin interface. Herein, the impedance between the electrode and the skin interface of three types of electrodes, which are the wet electrode, semidry electrode, and dry electrode, is investigated with electrochemical impedance spectroscopy combined with the spectra fitting technique. The parameters of performance duration, potential, and frequency associated with the impedance are explored for these three types of electrodes. The overall impedance is roughly constant within the performance duration and the potential applied in this study. Along with the frequency decreases, the impedance of the dry electrode reduces faster and is more complicated compared with the other two types of electrodes. Moreover, the results computed with the equivalent circuits show that the charge transfer resistance is additionally present compared to the wet and semidry electrodes. This large and additional charge transfer resistance may explain its relatively poorer electrophysiological properties.
A Novel Methodology for Lens Matching in Compact Lens Module Assembly

Lens matching is a trial assembly step in compact lens module manufacturing that can effectively improve the production yield and compensate for the manufacturing error to some degree. However, conventional lens matching (i.e., through trial and error (T&E)) is extremely time-consuming and has a low success rate. To address this issue, this paper proposes a novel Genetic Algorithm (GA) based solution to improve the assembly success rate and the efficiency of lens matching. The study first formalizes the lens matching problem into an optimization format. Then, a DNN based surrogate model is built to replace expensive optical simulators in the optimization iterations. The DNN is used because it demonstrates a great balance between prediction accuracy and computation efficiency compared to other alternatives, e.g., Linear Regression (LR), Kriging, and Polynomial Chaos Expansion (PCE). Next, a GA-based solver is developed to find optimal lens matching operations. The effectiveness of the proposed method and its superiority over conventional lens matching is validated in the real-world lens production line through collaboration with the industry. Compared with conventional lens matching, the proposed method can significantly improve the production yield and lens matching efficiency. Note to Practitioners—This paper is motivated by a practical need for lens matching in the manufacturing process of the image capturing compact lens modules. The conventional practice of lens matching is tedious, time-consuming, and easy to fail. To address this issue, we mathematically characterize the lens matching problem into an optimization format that can practically be solved by the Genetic Algorithm (GA) or other methods. We then demonstrate the workflow to search for optimal lens matching solutions based on a DNN surrogate model. Simulative studies and preliminary real-world experiments indicate the proposed method can effectively improve overall production yield and is much more efficient than conventional lens matching. The results in mass production further justified the superiority of the proposed method over conventional lens matching.
Study of teaching evaluation based on WeChat public platform

Teaching evaluation is an important part of the whole teaching process, it is a process of improving teaching. WeChat public platform is a new type of information push platform for a large number of users, simple and easy to use. Combined with the existing results of teaching evaluation, analyzes the educational function of WeChat public platform, which will be applied to teaching evaluation, propose the design idea of using the WeChat public platform to complete the teaching evaluation, which makes up for the deficiency of the traditional evaluation, provide new ideas for the application of the WeChat public platform to teaching.
Development of a hybrid solar wind turbine for sustainable energy storage

This thesis presents the design of hybrid solar wind turbine system for the power generation system by utilising both solar and wind renewable energy to the domestic household in the remote area which is unable to connect to the grid. The study was started by investigating the availability of both solar and wind energy in the desired location which is southern region of Malaysia. The design of wind turbine is modelling by Solidworks computer aided design (CAD) software. The computational fluid dynamics (CFD) is conducted by Solidworks Flow Simulation. The method of virtual wind tunnel simulation was adopted for wind turbine internal flow analysis with several of wind speed, in order to obtain the result of wind turbine performance in various levels of wind data. The data of solar radiation and wind speed were collected from the Malaysian Meteorological Department, then system configuration analysis done by simulation tool, HOMER. The basic requirement of electric primary load is determined in 12.06 kW per day for single household which is included the essential load demand such as lighting, computer and household appliance. The optimization analysis is conducted for generating most feasible system configuration and determines the quantity of components in the hybrid energy system, in order to meet the load demand of household and achieve the autonomy power supply with storing excess power generated in batteries storage for the sustainable energy storage.
Understanding how the network impacts performance and energy-efficiency in the RAMCloud storage system

In-memory storage systems emerged as a de-facto building block for today's large scale Web architectures and Big Data processing frameworks. Many research and engineering efforts have been dedicated to improve their performance and memory efficiency. More recently, such systems can leverage high-performance networks, e.g., Infiniband. To be able to leverage these systems it is essential to understand the trade-offs induced by the use of high-performance networks. This paper reports on work in progress aiming to contribute to a better understanding of the main factors impacting performance of in-memory storage systems. Through a study carried on RAMCloud, we focus on two settings: 1) clients are collocated within the same network as the storage servers (with Infiniband interconnects); 2) clients access the servers from a remote network, through TCP/IP. We compare and discuss aspects related to scalability and power consumption for these two scenarios which correspond to different deployment models for applications making use of in-memory cloud storage systems.
Human urinary kallidinogenase decreases the incidence of post-stroke cognitive impairment in acute ischemic stroke patients.

BACKGROUND Post-stroke cognitive impairment (PSCI) is a common symptom of stroke and affects the quality of life and prognosis of stroke survivors. In our study, we evaluated the efficacy of Human urinary kallidinogenase (HUK) on cognitive function in acute ischemic stroke (AIS) patients, and discussed the role of cystatin C (CysC) in improving PSCI. METHODS We enrolled a retrospective cohort with prospective follow-up. From August 2020 to May 2021, 130 patients completed the final follow-up. Among them, 61 patients received HUK combined with basic treatment, which we defined as the HUK group, and 69 patients received basic treatment, which we defined as the control group. We compared the changes of CysC, urea nitrogen and creatinine levels after one week of treatment between the two groups. Cognitive function was assessed by Montreal Cognitive Assessment (MoCA) at 3-month after AIS. RESULTS No significant differences in demographic data and Laboratory tests between two groups before treatment. A total of 67 patients (51.5%) were diagnosed as PSCI at 3-month follow-up, among which, 25 patients were in the HUK group and 42 patients were in the control group. Compared with the control group (60.9%), the incidence of PSCI was significantly lower in the HUK group (41.0%). In addition, the serum CysC level after a week of treatment significantly decreased from baseline in HUK group (p = 0.037), in comparison, the serum CysC level in the control group was basically unchanged (p = 0.951). There was a significant negative correlation between MoCA score and the level of CysC after treatment (p = 0.003, r = -0.373). CONCLUSIONS HUK can reduce the risk of PSCI at 3-month in AIS patients. The decrease of serum CysC level may be one of the mechanisms by which HUK reduces the incidence of PSCI.
Designer ‘blueprint’ for vascular trees: morphology evolution of vascular tissue constructs

Organ printing is a variant of the biomedical application of rapid prototyping technology or layer-by-layer additive biofabrication of 3D tissue and organ constructs using self-assembled tissue spheroids as building blocks. Bioengineering of perfusable intraorgan branched vascular trees incorporated into 3D tissue constructs is essential for the survival of bioprinted thick 3D tissues and organs. In order to design the optimal ‘blueprint’ for digital bioprinting of intraorgan branched vascular trees, the coefficients of tissue retraction associated with post-printing vascular tissue spheroid fusion and remodelling must be determined and incorporated into the original CAD. Using living tissue spheroids assembled into ring-like and tube-like vascular tissue constructs, the coefficient of tissue retraction has been experimentally evaluated. It has been shown that the internal diameter of ring-like and the height of tubular-like tissue constructs are significantly reduced during tissue spheroid fusion. During the tissue fusion process, the individual tissue spheroids also change their shape from ball-like to a conus-like form. A simple formula for the calculation of the necessary number of tissue spheroids for biofabrication of ring-like structures of desirable diameter has been deduced. These data provide sufficient information to design optimal CAD for bioprinted branched vascular trees of desirable final geometry and size.
Osmotic Adjustment and Antioxidant System Regulated by Nitrogen Deposition Improve Photosynthetic and Growth Performance and Alleviate Oxidative Damage in Dwarf Bamboo Under Drought Stress

Dwarf bamboo (Fargesia denudata) is a staple food for the endangered giant pandas and plays a critical role in the sub-alpine ecosystem. Characterized by shallow roots and expeditious growth, it is exceedingly susceptible to drought stress and nitrogen (N) deposition in the context of a changing global environment. However, a comprehensive picture about the interactive response mechanism of dwarf bamboo to the two factors, water regime and N deposition, is far from being given. Therefore, a completely randomized design with two factors of water regimes (well-watered and water-stressed) and N deposition levels (with and without N addition) of F. denudata was conducted. In view of the obtained results, drought stress had an adverse impact on F. denudata, showing that it destroyed ultrastructure integrity and induced oxidative damage and restricted water status in leaves and roots, as well as declined photosynthetic efficiency in leaves, especially in N non-deposition plants. Nevertheless, F. denudata significantly increased heat dissipation in leaves, regulated antioxidant enzymes activities, antioxidants contents, and osmoregulation substances concentrations in leaves and roots, as well as shifted biomass partitioning in response to drought stress. However, regardless of water availability, N deposition maintained better ultrastructure in leaves and roots, resulting in superior photosynthesis and growth of F. denudata. Additionally, although N deposition did not cause oxidative damage in well-watered plants, ameliorated the effects of drought stress on F. denudata through co-deploying heat dissipation in leaves, the antioxidant system in roots as well as osmotic adjustment in leaves and roots. Noticeably, the leaves and roots of F. denudata expressed quite distinct acclimation responses to drought resistance under N deposition.
Design and Analysis of Polarization Reconfigurable Microstrip Patch Antennas

The objective of work is to design and develop Polarization Reconfigurable Micro strip patch antenna which radiate electromagnetic wave of various orthogonal patterns. A progression of parametric study was done to get that how the features of the antenna depends on dimensions and material of geometry. Simulation of antenna has to be done by using CST microwave studio and HFSS. Antennas of various geometry have to be simulated and fabricated which radiates various orthogonal patterns of electromagnetic wave. The first antenna is to design and develop dual feed reconfigurable circularly polarized microstrip patch antenna feeding with microstrip line. By using switch and two feedline antenna is capable to radiate RHCP and LHCP. The second antenna is to design and develop reconfigurable circularly polarized microstrip antenna with single feed line, feeding with Proximity coupled method. Antenna is capable to radiate LHCP and RHCP with the help of proper switching action and reconfigurable feedline. The third design is to design and develop dual feed Quadri-Polarization States microstrip patch antenna feeding with microstrip line. With the help of two feedline and 4 diodes antenna is capable to radiate VLP, HLP, LHCP, RHCP. On the patch two opposite corners are slotted and connect by using two PIN diodes. The forth design is to design and develop polarization reconfigurable microstrip antenna with single feedline, feeding with microstrip line. Antenna is capable to radiate electromagnetic wave of various pattern like LP, LHCP, RHCP. Various S-parameters, surface current distribution, axial ratio, and radiation patterns are shown for various antennas. Antennas are capable to radiate various orthogonal patterns which increase the diversity gain. Therefore, antenna have a features of multipath effects reduction i.e. reduction of fading and interference and antenna can be used as polarization diversity array
THE EFFECT OF EARNING SURPRISE AND EARNING PER SHARE ON STOCK RETURN

A lot of investors are currently focusing on corporate earnings information, resulting on stock market reacts more strongly to unexpected earnings. The reaction is caused by several factors such as Earning Surprise (ES) and Earning per Share (EPS). Based on these, the research was conducted to find out how ES and EPS affect on stock return of manufacturing companies listed on Indonesia Stock Exchange in 2016-2018. This research is quantitative descriptive with associative research methods. The data used in this research were annual reports of manufacturing companies listed on the Indonesia Stock Exchange (IDX) during the period 2016-2018. Sampling in this research was conducted using a purposive sampling method. The results showed that simultaneusly and partially EPS and ES variables have no effect
An iterative algorithm of sub-array steered minimum variance

Large array has been widely used in underwater acoustic target detection, marine resources exploration and other fields due to its long detection distance and high azimuth resolution. Considering using steered minimum variance (STMV) algorithm in large array increases computational cost, and restricts its real-time implementation, an iterative algorithm of sub-array STMV (ISSMV) is proposed to permit real-time implementation on the limited computational resources. Theoretical analysis demonstrates that the proposed method can reduce the computational cost and eliminate the influence of strong coherent interference in weak target detection. The sea trial results show that the ISSMV algorithm maintains the high azimuth resolution of STMV and improves the ability of weak target detection while the computational cost of the proposed algorithm reduced sharply.