Real Side Research Articles

Mathematics behind the identifying CpG islands

The major objective of the paper is to review the theory for an hidden Markov model, a very general type of probabilistic model for sequences of symbols. In order for the hidden Markov model to be applicable to real-world applications, three key problems about the model must be addressed, and to do this, first we go over how to choose the best state sequence to explain an observation sequence, then we go over how to calculate the probability of an observation sequence, and finally we go over how to compute the maximization of the probability of the observation sequence. From these three angles, we review the mathematical concept behind the identification of CpG islands. The entire process and study of the outcomes have been tackled by examining both hypothetical and real DNA sequences side by side. We use well-known biological sequence analysis servers to carry out the experiment. Analytical and algorithmic approaches are compared while taking the hypothetical DNA sequence example into consideration.

The impact of energy price increases on the Polish economy

The aim of this paper is to assess the impact on the Polish economy of energy price shocks arising after the Russian invasion of Ukraine. We computed both the impact of the energy shocks (separately for gas, oil and coal prices) on the real side of the economy, and the pass-through of energy prices to the overall price level. The former part of the analysis was simulated using a computable general equilibrium (CGE) model of the Polish economy while the price effects of the shocks were simulated using a dual Leontief price model. Additionally, the price model was augmented with the mechanism of nominal wage adjustment suggested by the theory. This methodological novelty is our original contribution to empirical economics. Our simulations indicate that the price shock for all energy goods of the magnitude observed in 2022 resulted in a decrease in GDP of about 2.8% relative to the baseline solution. Moreover, we document a strong pro-inflationary effect of rising energy prices. After a combined shock to energy prices the consumption deflator increases by 10.3% (when we include the spreading the price increases across the industries), but the effect is simulated at 15.4%, when we account for an additional nominal wage adjustments (ensuring no real wage changes). We show that due to the differences in forward and backward propagation of shocks, the oil price shock had the strongest impact on real aggregates, whereas prices were hit the strongest by the gas price shock.

Can you hear me now? Identifying the effect of Chinese monetary policy announcements

Do Chinese monetary policy announcements matter? This study evaluates how relevant Chinese monetary policy announcements are to Chinese financial markets and the real side of the economy. Chinese monetary policy is identified by estimating a “target” factor measuring policy surprises and a “path” factor measuring future expectations of policy using price changes to Chinese financial derivatives on policy announcement dates. Local projection results show that 1) Chinese Treasury yields and interbank rates respond persistently, suggesting that policy transmission through an interest-rate channel exists; 2) Equities and exchange rates do not respond to policy announcements instantaneously, but with a lag; 3) Future expectations of Chinese monetary policy play a larger role than surprises, 4) Real variables show evidence of policy transmission, and 5) policy transmission may be sticky due to information frictions.

Borsa Istanbul Sectoral Connectedness Analysis

This study examines the volatility connectedness among banks, industrials, and services subindices of Borsa Istanbul using the Diebold-Yılmaz connectedness index methodology. The findings indicate that the banks index typically acts as a net receiver of connectedness from industrials and services indices. If the banks index is considered a proxy for the financial side of the Turkish economy while the other two represent the real side, this result aligns with earlier observations on the connectedness between the real and financial sides of economies. Specifically, it suggests that when a proxy for the real side incorporates financial variables, the real side tends to be a net source of connectedness most of the time. As shock propagators, industrials play a dominant role, and the banks index often moves in the opposite direction to the other two sectors.
 Key Words: Real and Financial Sectors, Financial Connectedness, Volatility, Borsa Istanbul.
 JEL Classification: C32, E44, G10.

Generating mutants of monotone affinity towards stronger protein complexes through adversarial learning

Despite breakthroughs achieved in protein sequence-to-structure and function-to-sequence predictions, the affinity-to-mutation prediction problem remains unsolved. Such a problem is of exponential complexity deemed to find a mutated protein or protein complex having a guaranteed binding-affinity change. Here we introduce an adversarial learning-based mutation method that creates optimal amino acid substitutions and changes the mutant’s affinity change significantly in a preset direction. The key aspect in our method is the adversarial training process that dynamically labels the real side of the protein data and generates fake pseudo-data accordingly to construct a deep learning architecture for guiding the mutation. The method is sufficiently flexible to generate both single- and multipointed mutations at the adversarial learning step to mimic the natural circumstances of protein evolution. Compared with random mutants, our mutated sequences have in silico exhibited more than one order of change in magnitude of binding free energy change towards stronger complexes in the case study of Novavax–angiotensin-converting enzyme-related carboxypeptidase vaccine construct optimization. We also applied the method iteratively each time, using the output as the input sequence of the next iteration, to generate paths and a landscape of mutants with affinity-increasing monotonicity to understand SARS-CoV-2 Omicron’s spike evolution. With these steps taken for effective generation of protein mutants of monotone affinity, our method will provide potential benefits to many other applications including protein bioengineering, drug design, antibody reformulation and therapeutic protein medication.

Transition and Integration Effects in the Baltic Housing Markets: The Dipasquale-Wheaton Approach

Abstract This paper analyses housing market developments in the Baltic States using a price-rent (PR) adjusted version of the DiPasquale-Wheaton (DPW) model as a frame of reference. Relating housing markets in Estonia, Latvia and Lithuania to the boom, the bust and the recovery after the financial crisis in 2007/2008, the paper discusses the interrelations between the different parts of the housing market system. Transition involves structural shifts, and the links between rental housing, owner-occupied housing and the housing construction industry might differ in the Baltics compared to mature economies, differences originating especially on the supply side of housing markets. As the Baltics are integrating their economies with the EU, housing markets may also be affected by the integration process, a process that includes factors both on the financial side and on the real side of the economy.

The real side of stock market exuberance: bubbles, output and productivity at the industry level

AbstractThere has been a growing interest in the theory of rational bubbles. Recent theories predict that bubbles are expansionary, but differ in the underlying mechanisms. This paper provides empirical evidence that helps us to assess different theories, and documents four main findings: stock market overvaluation is associated with (i) faster output and input growth, (ii) declining total factor productivity (TFP) growth, (iii) a greater contribution of labour and a declining contribution of TFP for output growth, (iv) an increase in the number of firms. Overall, these findings suggest that bubbly expansions are driven by increased factor accumulation (in particular labour), and not from higher productivity growth.

Transition to professional practice: Perspectives of new nursing graduates of Nepal.

Internationally, the transition from student nurse to practicing nurse is recognized as being the most stressful period. Yet very little is known about how new nursing graduates perceive this transition in Nepal. The study aimed to explore new nursing graduates' perceptions of the transition to professional practice. A qualitative descriptive methodology was used. In-depth semi-structured interviews were conducted with 10 purposively recruited participants from two private hospitals in Nepal. Data were analyzed using inductive thematic analysis. The Consolidated Criteria for Reporting Qualitative Research (COREQ) guidelines were used to report the findings of this study. New nursing graduates perceived the transition to professional practice as an intense experience. Inductive thematic analysis yielded four intrinsically linked themes that encompassed new nursing graduates' transition experiences: 'getting hit by reality', 'losing confidence', 'feeling unsupported', and 'gathering strengths.' The theme 'getting hit by reality' included three sub-themes: 'gap between theory and practice,' 'no protective shield,' and 'plethora of responsibilities', which explains nurses' initial encounter with real-world practice. The theme 'losing confidence' contained three sub-themes: 'being fearful,' 'being ignored,' and 'being accused,' which describes how nurses started losing confidence as they confronted the real side of the profession. The theme 'feeling unsupported' included two sub-themes: 'left without guidance,' and 'limited support from seniors,' which explains how nurses perceived their work environment. The theme 'gathering strength' contained two sub-themes: 'reflecting' and 'asking for help,' which describes how nurses coped with the challenges related to the transition. To facilitate the transition to practice, educational institutions must impart to students a realistic understanding of the transition process, address the theory-practice gap, and collaborate with hospitals. Similarly, hospitals should have realistic expectations from new nurses, assign work according to their capabilities, and allow them sufficient time for role integration. Likewise, well-conceived detailed orientation, mentorship or preceptorship programs, and regular professional development programs are vital to easing the transition. Furthermore, establishing and maintaining a supportive work culture, which promotes equity, respect, and safety among employees, is crucial for positive transition experiences.

Active living wall for particulate matter and VOC remediation: potential and application.

Particulate matters (PM) and volatile organic compounds (VOCs) are the sources of toxic substances that hurt human health and can cause human carcinogens. An active living wall was applied to reduce PM and VOC contamination, while Sansevieria trifasciata cv. Hahnii, a high-performance plant for VOC removal, was selected to grow on the developing wall and used to treat PM and VOCs. The active living wall operating in a 24 m3 testing chamber showed the ability to remediate more than 90% PM within 12h. The VOC removal can be approximately 25-80% depending on each compound. In addition, the suitable flow velocity of the living wall was also investigated. The flow rate of 1.7 m3h-1 in front of the living wall was found as the best inlet flow velocity for the developed active living wall. The suitable condition for PM and VOC removal in the active living wall application on the real side was presented in this study. The result confirmed that the application of an active living wall for PM phytoremediation can be an alternative effective technology.

How to Fold a Triangle: The Connection between the Grashof Fourbar Linkage and Pythagorean Triangles

Summary This paper presents two different methods for folding a triangle onto a flat line by converting it into a Grashof Special Case fourbar linkage. Foldable triangles have many applications, ranging from space structures to collapsible furniture. In the first method, a generic triangle with positive real side lengths is shown to be foldable inward and outward by adding a pin joint at a specific location to one of the sides. The second method shows how to create a collapsible linkage using a Pythagorean triangle; we demonstrate that all four links in the Pythagorean fourbar have integer length and can be easily built using rods with uniformly spaced holes (e.g., LEGO bricks, Unistrut, etc.). Next, the formulas for finding the interior angles of the Pythagorean fourbar are presented, for the purpose of plotting collapsible structures with mathematical software. We conclude with a demonstration of a sample application of Pythagorean fourbars to collapsible arch or tower structures and a surprising proof that some types of collapsible arch structures are unrealizable with Pythagorean fourbars.

Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images.

Background Reducing the amount of contrast agent needed for contrast-enhanced breast MRI is desirable. Purpose To investigate if generative adversarial networks (GANs) can recover contrast-enhanced breast MRI scans from unenhanced images and virtual low-contrast-enhanced images. Materials and Methods In this retrospective study of breast MRI performed from January 2010 to December 2019, simulated low-contrast images were produced by adding virtual noise to the existing contrast-enhanced images. GANs were then trained to recover the contrast-enhanced images from the simulated low-contrast images (approach A) or from the unenhanced T1- and T2-weighted images (approach B). Two experienced radiologists were tasked with distinguishing between real and synthesized contrast-enhanced images using both approaches. Image appearance and conspicuity of enhancing lesions on the real versus synthesized contrast-enhanced images were independently compared and rated on a five-point Likert scale. P values were calculated by using bootstrapping. Results A total of 9751 breast MRI examinations from 5086 patients (mean age, 56 years ± 10 [SD]) were included. Readers who were blinded to the nature of the images could not distinguish real from synthetic contrast-enhanced images (average accuracy of differentiation: approach A, 52 of 100; approach B, 61 of 100). The test set included images with and without enhancing lesions (29 enhancing masses and 21 nonmass enhancement; 50 total). When readers who were not blinded compared the appearance of the real versus synthetic contrast-enhanced images side by side, approach A image ratings were significantly higher than those of approach B (mean rating, 4.6 ± 0.1 vs 3.0 ± 0.2; P < .001), with the noninferiority margin met by synthetic images from approach A (P < .001) but not B (P > .99). Conclusion Generative adversarial networks may be useful to enable breast MRI with reduced contrast agent dose. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Bahl in this issue.

Macro-financial spillovers

We analyse spillovers between the real and financial sides of the US economy, and between those in the US and other advanced economies. The approach developed allows for differences in sampling frequency between financial and macroeconomic data. We find that financial markets are typically net transmitters of shocks to the real side of the economy, particularly during turbulent market conditions. This result holds both for domestic US macro-financial spillovers, and also those between the US and other advanced economies. Our macro-financial spillover measures are found to have significant predictive ability for future macroeconomic conditions in both in-sample and out-of-sample forecasting environments. Furthermore, the predictive ability frequently of our macro-financial measures frequently exceeds that of purely financial systemic risk measures previously employed in the literature for the same task.

A novel single phase grid connected solar photovoltaic system for state of charge estimation using recurrent neural networks

ABSTRACT Renewable energy (RE) resources have reached the top-notch state in satisfying the energy demands of recent days. Solar photovoltaic (PV) is considered as a clean form of energy among the various RE resources. A novel single-phase grid-integrated solar PV system with Re-lift Luo converter with aid of a chicken swarm (CS) optimization algorithm is presented. The Re-lift Luo converter is implemented as it has maximum power density, extreme efficacy, high-voltage-gain ratio, and reduced switching losses. Since the PV output is intermittent, the output of the converter also gets varied, which will be maintained constant by implementing a proportional–integral (PI)-based closed loop control through the optimized CS algorithm. The normalized output is further applied to the grid via single-phase voltage source inverter. A battery is utilized to store the daytime’s solar energy and discharges to the grid during the night time. The monitoring of the battery’s state of charge (SoC) is performed by recurrent neural network (RNN). A PI controller achieves the real and reactive grid side power control. The novelty of the proposed work is the utilization of three control strategies such as PI, CS, and RNN in improving the overall performance of a grid connected system in improving the power quality. Proper control and analysis of the converters and battery through intelligent controllers are the major objectives of the paper. The outcome of the proposed concept reigns in the improvement of power quality and the proper estimation of SoC, which was supported by the detailed simulation and experimental studies. The proposed configuration is verified by simulation in MATLAB/Simulink and also tested in a real-time experimental setup, and the obtained results are as per the IEEE standards.

Number of creditors and the real effects of credit supply disruptions

This paper examines the role of bank-firm relationships in transmitting credit supply shocks to the real side of the economy in an emerging market. Using a hand-collected dataset for Iranian public companies, we exploit firms' exposure to a bank involved in a massive Ponzi scheme in 2011. We document a nearly 8 percentage point drop in annual employment growth rate for firms connected to the troubled bank following the credit dry-up caused by the scandal. We show that the magnitude of the effect on employment and investment is amplified by bank-firm relationship at least as much as by the financial constraint status found in previous studies. The results highlight the role of bank-firm relationships and the importance of access to multiple creditors in alleviating the consequences of credit supply disruptions.

THE CONCEPT OF IDENTITY DEPICTED BY MARGO IN JOHN GREEN’S PAPER TOWN

This study aims to analyze Margo’s Identity in John Green’s Paper Town. The primary source is the novel Paper Town by John Green. To analyze the problems formulated above, the writer uses the theory of identity from Erik Erikson. The result of the study is Margo is an introverted person. She does not like to share her feelings with others. She always keeps her problems to herself. It makes other people create their perspectives about her and she cannot show her real side of her. Margo is also a smart girl. When she is a child, she does an investigation about the dead man. She manipulates the police and the woman in the apartment so she can get information about the dead man. Her decision to leave the town and never want to come back is a big decision. Her parents, sister, friends, and all the people live in that town, but she chooses to leave all of them forever. When she finds out her boyfriend is cheating on her with her best friend, she starts to change her way of thinking. The finding of this thesis is identity is developed by individuals, but must be recognized and confirmed by others. In Paper Towns, those that are idealized are done so in a positive light. If people have a negative outlook on generalized portions of life, then when faced with individual forms, their negative outlook will translate and prevent people from truly being honest about whether something is good or bad for their identity.

TEXTUAL ANALYSIS OF THE COP AND THE ANTHEM FROM THE PERSPECTIVE OF FUNCTIONAL STYLISTIC

As the most influential theory in the last 20th century, Systemic Functional Linguistics provided a brand new perspective for analysis of literary works. This theory enables the linguistics and scholars to analyze language concisely and deeply. The Cop and the Anthem, as one of O. Henry’s famous short story, revealed the real side of American society in humorous language. This paper interprets the text of the Cop and the Anthem from the perspective of Functional Stylistic to analyze its language expression characteristics, plot setting and full-text cohesion. It’s expected to provide reference for the functional stylistic analysis of relevant types of short stories.

Deep learning based real time Demand Side Management controller for smart building integrated with renewable energy and Energy Storage System

Electric Power Consumption (EPC) and Renewable Energy Generation (REG) are inconsistent and this fickle nature affects the utility grid's power quality and system stability. The electric transmission and distribution infrastructure must be upgraded to meet the consumer's peak demand. Hence, proposing a Demand Side Management (DSM) program in smart grid to reduce utility grids Peak to Average Ratio (PAR) and end-users electricity tariff. Renewable energy with Energy Storage System (ESS) in the DSM controller is used to enhance the end user's economic and environmental features. This article proposes a Recurrent Neural Network (RNN) based Long Short Term Memory (LSTM) framework for Science Block (SCB) every minute and 5 min of EPC and REG forecasting to develop the DSM program. This proposed deep learning model performance, is evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and R-squared. The results show that the proposed DSM program benefits end electricity users and smart grid operators.

Role of Main Stream Western Media in Peace Building and Conflict Prevention in Muslim Societies: Analytical Study in Contemporary Scenario

Media has a major role in conflicted the news we see and hear. Journalists use different mass media in shaping their news and presenting it to the world. In the Muslim societies, conflict preservation and peace building is important to understand the values and media dynamics in making decisions for spreading peace on the news channels and entertainment. Media is a source of inciting towards violence. It is an acceptable tool for the audience in getting updates about the world. Media act as an interpreter in making people dependent on it. With the technological advancement, it has become a major part of our daily entertainment and communication source. Being a gatekeeper, it portrays balance view, filter the issues and set agendas to provide entertainment to the world. Muslim societies are badly affected by the media in case of reputation. Muslims are low graded in the entire world because of Taliban’s and other terrorists. Media is a source of building peace for the Muslim societies in the world. By showing the right side of the Muslim societies, the world would be able to accept and love Muslims all around the world. Media can work on peace negotiation and mobilize people support in creating peace and preventing conflicts for the Muslim societies. The aim of achieving a peace-built life is to create positive relations all around the world and it could only be done through the media. Media is a very big source of spreading peace, positivity and preventing conflicts regarding the Muslim society. Successful media campaigns can be done to show the real side of Muslims and make the world aware about the real Muslim societies. To achieve this change, many worldwide Islamic organizations can cooperate on media to disseminate on peace agreement information. There would be many acceptable experiences change regarding peace building and conflict prevention for the Muslim societies.

A convenient demand response layout for energy efficient residential prosumers

Demand response (DR) is a high priority smart grid technology yet, efficient implementation of the same at the circuit level is often overlooked. Technologies like DR is vital to the improvement, stability and reduction of congestion in the grid. At the distribution side, addition of photovoltaic (PV) systems with appropriate metering has made consumers to prosumers. Prosumers contribute to the grid supply and often meeting increased demand. PV installation has made surplus grid power available. Power from PV is an environment friendly approach, in-order to yield its maximum benefit, it should be appropriately connected with advanced metering infrastructure (AMI). Further, AMI enables other technologies like real time pricing (RTP), DR and demand side management (DSM). Pilot projects put forward by Government of India (GOI) has already deployed smart meters, transforming existing conventional meters into AMI. Hence, functional benefits of AMI are to be studied to its full usage potential. DR and RTP are more focused on consumer behaviour and involvement whereas, DSM is under the control of utility. Hence, novel layouts for energy efficient prosumers with net-metering, gross-metering, hybrid loads and renewable PV integration are analysed. Consumer feasibility of DR without compromising, basic needs of power availability and comfort is focused. Inference is made from both metering infrastructures, tariff schemes and its application in Puducherry locality of India.

Financial Stability and Economic Activity in China: Based on Mixed-Frequency Spillover Method

To improve financial sustainability and promote economic stability, it is important to understand the intricate relationship between finance and macroeconomy. Thus, focusing on financial stress and macroeconomic sectors, this paper investigates macro-financial spillovers in China. First, we develop a high-frequency financial stress index based on eight daily financial indicators to measure the stability of China’s financial markets. Through event identification, we find that China’s Financial Stress Index can effectively reflect the stress situation of China’s financial market. Then, given that the traditional co-frequency method fails to deal with financial stress index and macroeconomic data with different frequencies, we employ the mixed-frequency spillover method to evaluate macro-financial spillovers to examine the connectedness between China’s financial market and the real side of the economy. We find that financial stress is the leading net risk output and primarily affects the loan sector; deterioration of economic conditions can lead to more apparent fluctuations in spillover effects, with spillovers from financial stress to others being the most susceptible; within the sample, the 2015 stock crash, U.S.–China trade friction, and COVID-19 have the most impact on macro-financial spillover effects. In addition, we track the results of different risk events on spillover effects across sectors.