Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Stock Price Changes Based on the Limit Order Book: A Survey

This survey starts with a general overview of the strategies for stock price change predictions based on market data and in particular Limit Order Book (LOB) data. The main discussion is devoted to the systematic analysis, comparison, and critical evaluation of the state-of-the-art studies in the research area of stock price movement predictions based on LOB data. LOB and Order Flow data are two of the most valuable information sources available to traders on the stock markets. Academic researchers are actively exploring the application of different quantitative methods and algorithms for this type of data to predict stock price movements. With the advancements in machine learning and subsequently in deep learning, the complexity and computational intensity of these models was growing, as well as the claimed predictive power. Some researchers claim accuracy of stock price movement prediction well in excess of 80%. These models are now commonly employed by automated market-making programs to set bids and ask for quotes. If these results were also applicable to arbitrage trading strategies, then those algorithms could make a fortune for their developers. Thus, the open question is whether these results could be used to generate buy and sell signals that could be exploited with active trading. Therefore, this survey paper is intended to answer this question by reviewing these results and scrutinising their reliability. The ultimate conclusion from this analysis is that although considerable progress was achieved in this direction, even the state-of-art models can not guarantee a consistent profit in active trading. Taking this into account several suggestions for future research in this area were formulated along the three dimensions: input data, model’s architecture, and experimental setup. In particular, from the input data perspective, it is critical that the dataset is properly processed, up-to-date, and its size is sufficient for the particular model training. From the model architecture perspective, even though deep learning models are demonstrating a stronger performance than classical models, they are also more prone to over-fitting. To avoid over-fitting it is suggested to optimize the feature space, as well as a number of layers and neurons, and apply dropout functionality. The over-fitting problem can be also addressed by optimising the experimental setup in several ways: Introducing the early stopping mechanism; Saving the best weights of the model achieved during the training; Testing the model on the out-of-sample data, which should be separated from the validation and training samples. Finally, it is suggested to always conduct the trading simulation under realistic market conditions considering transactions costs, bid–ask spreads, and market impact.
Enhanced Light Extraction from Organic Light-Emitting Diodes with Micro-Nano Hybrid Structure

In this study, an external light extraction layer with a micro-nano hybrid structure was applied to improve the external light extraction efficiency of organic light-emitting diodes (OLEDs). A reactive ion-etching (RIE) process, using O2 and CHF3 plasma, was performed on the surface of the micro-scale pattern to form micro-nano hybrid structures. According to the results of this study, the nanostructures formed by the treatment of O2 and CHF3 were different, and the efficiency according to the structures was analyzed experimentally and theoretically. As a result, the OLED, to which the micro-nano hybrid structure, manufactured through a simple process, is applied, improved the external light extraction efficiency by up to 38%, and an extended viewing angle profile was obtained. Additionally, an effective method for enhancing the out-coupling efficiency of OLEDs was presented by optimizing the micro-nano hybrid structure according to process conditions.
Beyond fill and spill: Hydrological connectivity in a sub‐arctic bog‐fen‐tributary complex in the Hudson Bay Lowlands, Canada

Patterned bog and fen peatlands, which dominate the landscape in the Hudson Bay Lowlands (HBL), act as important water storage and conveyance features in this region. In spite of their hydrological importance, there are currently no studies that define and characterize the thresholds of bog‐fen‐tributary hydrological connectivity in the HBL or their relation to seasonal and annual changes in water fluxes. To this end, hydrological (i.e., streamflow and groundwater levels) and meteorological (i.e., precipitation, snow depth, evapotranspiration, and temperature) data were collected at a 4.8 km2bog‐fen‐tributary complex between 2007 and 2018. Connectivity thresholds were best characterized into three states (disconnected, connected, and high activity) that incorporated 41%, 47%, and 12% of the study period and 4%, 18%, and 78% of runoff, respectively. Runoff generally peaked in the spring due to snowmelt, while connectivity was highest in the peatlands in the fall months when precipitation exceeded evapotranspiration due to cooling temperatures. Warmer than average spring temperatures accelerated snowmelt rate faster than frost table thaw rate in the fen; this reduced the amount of meltwater that entered storage, increased drainage from bog to fen, and decreased overall connectivity in the unfrozen season. Cooler than average spring temperatures delayed bog connection and ground thaw; the late frost melt provided a source of water to the bogs after melt into the late spring and early summer. This study provides a basis for the modelling of peatland hydrological connectivity in the region in the drier conditions anticipated with climatic warming and regional resource extraction.
Factors influencing stone-free rate of Extracorporeal Shock Wave Lithotripsy (ESWL); a cohort study

Abstract Objective To evaluate the success rate of Extracorporeal Shock Wave Lithotripsy (ESWL) therapy and identify relevant treatment-specific factors affecting stone-free rate (SFR) after ESWL. Materials and methods All ESWL treatments in the years 2016–2019, in Ängelholm Hospital, Skåne, Sweden were analysed retrospectively. Primary outcome was stone-free rate (SFR) at 3 months. Univariate logistic regression was used followed by multivariable regression. Lasso analysis was made to adjust for treatment-specific factors such as age, stone size, skin-to-stone distance (SSD), stone attenuation, number of treatments, stone location and presence of a urinary stent. Results Factors affecting successful ESWL treatment were lower age (p < 0.001), smaller stone size and volume (both p = 0.001). SSD, stone attenuation, sex, laterality and drainage did not have an effect on SFR in this study. After the first ESWL treatment session, 46.7% of the patients were stone-free. Conclusion Results indicate that stone size and age are the most predictive factors for ESWL outcome. Based on this, we present a simple model for prediction of SFR after ESWL, to be used when counseling patients before ESWL treatment.
Flavonoids for depression and anxiety: a systematic review and meta-analysis

Abstract Natural flavonoids are the most plentiful form of polyphenols. Given the anti-inflammatory and antioxidant properties of flavonoids, researchers discovered that it might be effective in treating depression and anxiety. The effect of flavonoids on depression and anxiety was investigated by a meta-analysis and systematic review. We searched PubMed, Embase, and Medline databases up to October 15, 2021. We selected 11 studies, among them, 10 studies were chosen to evaluate the depression effects of flavonoids and 7 studies were used to assess anxiety disorder. The meta-analysis showed that flavonoids have an overall significant effect on depression (p = 0.004, Hedge’s g = −0.487, 95% CI −0.814 to −0.160) and anxiety (p = 0.006, Hedge’s g = −0.741, 95% CI −1.266 to −0.217). Subgroup analysis indicated that the symptoms of depression were significantly improved in the studies when the dose of flavonoids was 50-100mg/day or the treatment duration was ≥8weeks. Anxiety symptoms were improved in the studies with the dose of flavonoids was ≥50mg/day. There was no evidence of publication bias. Our findings suggest that flavonoids might improve symptoms of depression and anxiety. However, a small number of participants and studies were included in this meta-analysis. Therefore, the results should be interpreted with caution.
Comprehensive Review on Misbehavior Detection for Vehicular Ad Hoc Networks

Vehicular ad hoc networks (VANETs) can increase road safety and comfort. It needs strong demand for security because the data sent in VANETs influence vehicles’ behavior. Existing studies have summarized VANET security, challenge, and attacks. This study aims to present a comprehensive overview of misbehavior detection in VANETs. First, VANET characteristics, security issues, and attacks are discussed. Then, the precise definition of misbehavior, detection mode, and detection objects are presented. Generic misbehavior detection is classified as data-centric and node-centric. In this study, to adapt to the VANETs scenario, we proposed a novel taxonomy of misbehavior detection, which considers the interaction between vehicles and which is refined by emphasizing the detection modes and participants. Finally, the remaining concerns, open issues, and prospective future research directions are discussed.
Prosecuting rap: what does the case law tell us?

Abstract This article explores the admissibility and use of rap music as evidence in English criminal trials. It presents findings from an analysis of over 30 appeal cases. As well as unpacking the link between rap, race and gangs that is prevalent in these cases, the article challenges the categorisation of rap as ‘bad character evidence’, and critiques the way in which questions of relevance and prejudicial effect have been addressed by the courts. In particular, when making admissibility decisions, the courts appear to give little consideration to the cultural context, artistic conventions or social influences within the rap music genre, or the racialised nature of rap evidence. It is argued that, if rap is to be admissible evidence, a much more rigorous and informed approach is required.
Impact of Combined Bifrontal Transcranial Direct- Current Stimulation and Conflict Processing Training on Tinnitus: a Protocol for Single-Blind Randomized Controlled Trial

Background and Aim: The deficit in cognitive functions and central executive function is one of the popular hypotheses on the underlying cause of tinnitus. These factors are not only the complications of tinnitus but are also involved in the generation of it. In this study, bifrontal transcranial Direct Current Stimulation (tDCS) and conflict processing will be used in the form of auditory Stroop training to improve cognitive performance and inhibition control for tinnitus management. Methods: This study will be carried out on 34 chronic tinnitus patients. The initial evaluations include the tinnitus psychoacoustic evaluations, determination of the tinnitus handicap through tinnitus handicap inventory, and examining the annoyance and loudness of tinnitus through the visual analog scale after which the participants will be investigated in two groups. The first group will receive sessions of tDCS followed by six sessions of conflict processing training. The second group will first receive tDCS in the form of sham, to be followed by six sessions of auditory Stroop. The evaluations will be repeated after each intervention. Discussion: Studies have shown that successive sessions of conflict processing training can enhance cognitive plasticity and inhibition function. As conflict processing training has not been addressed as rehabilitation training in the people suffering from tinnitus, these processes will be designed in four tasks as rehabilitation exercises in Farsi language and applied along with tDCS to the people with chronic tinnitus to decrease and control tinnitus by improving cognitive and inhibition control. Trial registration: Iranian Registry of Clinical Trials (IRCT20120215009014N366) on Sep 17th, 2020. Keywords: Tinnitus; conflict processing; Stroop training; inhibition
Training Monitoring in Sports: It Is Time to Embrace Cognitive Demand

Appropriate training burden monitoring is still a challenge for the support staff, athletes, and coaches. Extensive research has been done in recent years that proposes several external and internal indicators. Among all measurements, the importance of cognitive factors has been indicated but has never been really considered in the training monitoring process. While there is strong evidence supporting the use of cognitive demand indicators in cognitive neuroscience, their importance in training monitoring for multiple sports settings must be better emphasized. The aims of this scoping review are to (1) provide an overview of the cognitive demand concept beside the physical demand in training; (2) highlight the current methods for assessing cognitive demand in an applied setting to sports in part through a neuroergonomics approach; (3) show how cognitive demand metrics can be exploited and applied to our better understanding of fatigue, sport injury, overtraining and individual performance capabilities. This review highlights also the potential new ways of brain imaging approaches for monitoring in situ. While assessment of cognitive demand is still in its infancy in sport, it may represent a very fruitful approach if applied with rigorous protocols and deep knowledge of both the neurobehavioral and cognitive aspects. It is time now to consider the cognitive demand to avoid underestimating the total training burden and its management.
Aliança de trabalho em aconselhamento de carreira: Fatores dos/as psicólogos/as e clientes

A aliança de trabalho é um preditor da eficácia da intervenção psicológica e envolve o trabalho colaborativo entre psicólogo/a e cliente. Neste estudo, analisa-se em que medida a experiência profissional dos/as psicólogos/as, o rendimento económico e a (in)decisão do/da cliente predizem a aliança de trabalho inicial e se esses fatores e a aliança inicial predizem a aliança final. Participaram 49 clientes do aconselhamento de construção da carreira, com idade entre os 17 e os 52 anos e sete psicólogas. Utilizou-se um questionário sociodemográfico, a Escala de Decisão de Carreira e o Inventário da Aliança Terapêutica. Resultados de análises de regressão linear múltipla indicam a experiência profissional dos/as psicólogos/as e o rendimento económico dos/as clientes como preditores da aliança inicial. A experiência profissional dos/as psicólogos/as, a indecisão final dos/as clientes e a aliança inicial predizem a aliança final. Os resultados deste estudo são discutidos, retirando-se implicações para a investigação e prática.
Crossing the Blood-Brain Barrier: Advances in Nanoparticle Technology for Drug Delivery in Neuro-Oncology

The blood-brain barrier (BBB) constitutes a microvascular network responsible for excluding most drugs from the brain. Treatment of brain tumors is limited by the impermeability of the BBB and, consequently, survival outcomes for malignant brain tumors remain poor. Nanoparticles (NPs) represent a potential solution to improve drug transport to brain tumors, given their small size and capacity to target tumor cells. Here, we review the unique physical and chemical properties of NPs that aid in BBB transport and discuss mechanisms of NP transport across the BBB, including paracellular transport, carrier-mediated transport, and adsorptive- and receptor-mediated transcytosis. The major types of NPs investigated for treatment of brain tumors are detailed, including polymeric NPs, liposomes, solid lipid NPs, dendrimers, metals, quantum dots, and nanogels. In addition to their role in drug delivery, NPs can be used as imaging contrast agents and can be conjugated with imaging probes to assist in visualizing tumors, demarcating lesion boundaries and margins, and monitoring drug delivery and treatment response. Multifunctional NPs can be designed that are capable of targeting tumors for both imaging and therapeutic purposes. Finally, limitations of NPs for brain tumor treatment are discussed.
Squeezed: The impact of Covid-19 on Mozambican agriculture

The world is facing a pandemic of an unprecedented nature. By the end of October 2020, the Covid-19 pandemic had claimed over a million lives and forced lockdowns across the world. People were restricted in their movements and economies around the world are still in limbo. This article analyzes the impacts of Covid-19 on the Mozambican agricultural sector by the end of 2020 when the pandemic was still a novelty and there were no vaccines available. Using secondary data analysis and interviews, this paper argues that the agricultural sector, especially cash crops, has been pressured by a combination of pre-existing factors, including weather conditions, terrorist attacks, and the financial crisis, which were, then, exacerbated by the new challenges presented by Covid-19. The direct effects of Covid-19 on the Mozambican agricultural sector were (1) a limitation on imports of essential agricultural inputs such as seeds, pesticides and fertilizers, and (2) a considerable reduction in the production and export of cash crop products. In addition, we found that food crops, which are less dependent on the global market, were less impacted. Nevertheless, the long-term impacts remain unclear, and more research is needed to provide a comprehensive understanding. Based on the results, we recommend that the impacts of Covid-19 be analyzed and better understood using a holistic approach that integrates data on pre-existing conditions and their dynamics to model future scenarios. Finally, we recommend expanding investments in local production of essential agricultural inputs such as fertilizers, improved seeds and pesticides.
IMPROVING THE PERFORMANCE OF HYBRID MAIN MEMORY THROUGH SYSTEM AWARE MANAGEMENT OF HETEROGENEOUS RESOURCES

Modern computer systems feature memory hierarchies which typically include DRAM as the main memory and HDD as the secondary storage. DRAM and HDD have been extensively used for the past several decades because of their high performance and low cost per bit at their level of hierarchy. Unfortunately, DRAM is facing serious scaling and power consumption problems, while HDD has suffered from stagnant performance improvement and poor energy efficiency. After all, computer system architects have an implicit consensus that there is no hope to improve future system’s performance and power consumption unless something fundamentally changes. To address the looming problems with DRAM and HDD, emerging Non-Volatile RAMs (NVRAMs) such as Phase Change Memory (PCM) or Spin-Transfer-Toque Magnetoresistive RAM (STT-MRAM) have been actively explored as new media of future memory hierarchy. However, since these NVRAMs have quite different characteristics from DRAM and HDD, integrating NVRAMs into conventional memory hierarchy requires significant architectural re-considerations and changes, imposing additional and complicated design trade-offs on the memory hierarchy design. This work assumes a future system in which both main memory and secondary storage include NVRAMs and are placed on the same memory bus. In this system organization, this dissertation work has addressed a problem facing the efficient exploitation of NVRAMs and DRAM integrated into a future platform’s memory hierarchy. Especially, this dissertation has investigated the system performance and lifetime improvement endowed by a novel system architecture called Memorage which co-manages all available physical NVRAM resources for main memory and storage at a system-level. Also, the work has studied the impact of a model-guided, hardware-driven page swap in a hybrid main memory on the application performance. Together, the two ideas enable a future system to ameliorate high system performance degradation under heavy memory pressure and to avoid an inefficient use of DRAM capacity due to injudicious page swap decisions. In summary, this research has not only demonstrated how emerging NVRAMs can be effectively employed and integrated in order to enhance the performance and endurance of a future system, but also helped system architects understand important design trade-offs for emerging NVRAMs based memory and storage systems.
Predictors of Neurodevelopmental Outcome in Hyperbilirubinemic Neonates Admitted in NICU

Background: Neonatal hyperbilirubinemia is an important cause of preventable brain damage among infants. Neurodevelopmental assessment may help in the early identification and management of neurodevelopmental sequelae. Objectives: The aim of this study were to identify J Pediatr Perinatol Child Health 2022; 6 (2): 200-218 DOI: 10.26502/jppch.74050102 Journal of Pediatrics, Perinatology and Child Health 201 the predictors of abnormal neurodevelopment at 3 & 12 months in babies having birth weight ≥1800 g and gestational age >34 weeks with neonatal hyperbilirubinemia. Methods: This prospective observational study was conducted at Department of Neonatology and Institute of Pediatric Neurodisorder and Autism (IPNA), Bangabandhu Sheikh Mujib Medical University (BSMMU), Shahbag, Dhaka, Bangladesh from July 2019 to June 2021. Hyper-bilirubinemic newborns were followed up and their neurodevelopmental assessment was done by using BSID III method at 3 and 12 months of age. All the collected data was tabulated and statically analyzed by using SPSS software. Results: A total of 90 newborns were enrolled, and among them 72 completed the first follow up and 67 completed second follow up. Average gestational age was 37.28±1.4 and mean birth weight was 2870.97 ± 458 g. There was slight female predominance 42 (58.3%) and 69 (95.8%) babies were inborn and only 3 (4.2%) were outborn. Out of 72 neonates, 9 (12.5%) had abnormal neurodevelopment results at 3 months, whereas 2 (3%) had neurodevelopmental abnormalities at 12 months. Neurodevelopmental follow up is suggesting reversibility of adverse neurodevelopment outcome. Perinatal and clinical data were compared between age appropriate neurodevelopment group and delayed neurodevelopment group. This study found that hemolytic jaundice, need for exchange transfusion, jaundice within first 24 hours, peak serum bilirubin > 20 mg/dl and longer duration of phototherapy > 48 hours were not significantly associated with abnormal neurodevelopment. Conclusion: 9 (12.5%) and 2 (3%) had abnormal neurodevelopment at 3 months and at 12 months respectively who were treated for neonatal jaundice suggesting reversibility of adverse neurodevelopment outcome. None of the factors (eg. hemolytic neonatal jaundice, onset of jaundice within 24 hours of age, peak serum bilirubin levels >20mg/dl, need for exchange transfusion and duration of phototherapy >48 hours were significantly not associated with adverse neurodevelopmental outcomes in infants born at or near term.