Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterization of rock layers based on seismic refraction method : a case study of Mentarang ’ s Hydro ‐ power Plant , Malinau Regency , North Kalimantan

North Kalimantan Province is a new province that is dynamic in development in order to prosper the inhabitants. The research and exploration to make a plan to develop new renewable energy are one of their main programs. The hydro-power plant of Mentarang, Malinau Regency, Kalimantan Utara is a plan program in 2020. The research study of hydro-power plants is essential as a reference in the development plan and avoids the hazard, miss calculation due to human error, etc. Seismic refraction is used in the feasibility study and detailed engineering study (FS DED) of Mentarang's Hydro-power plant. Analysis from the Seismic refraction method can be used as an input parameter for deciding the feasibility of Mentarang's hydro-power plant. This study aims to characterize the sub-surface layers, structure, and sub-surface layer thickness within this area. The seismic refraction method uses the intercept time or travel-time versus distance and processed using the reciprocal method, then it is modelled using inversion and resulted in a 2D profile. This research study was used the seismic refraction method with geometry acquisition of 14 sources with two spread and 5 meters of geophone interval. The analysis result of the 2D inversion profile model, in general, is classified as four strata layers. These strata are categorized as weathered layers with 5-15 meters of thickness, clay, and Sandstone about 5-20 meter of layer thickness, Sandstone with the layer thickness of about 20-50 meters, and lastly, granite, lava rocks, or limestone with depth more than 70 meters below the subsurface. There is a possibility of a structure at an offset of 70 meters, but this method's limitation will overestimate the conclusion. Therefore, it is necessary to bring another method that more sensitive to work further in research study evaluation of hydro-power plant Mentarang, Malinau Regency, North Kalimantan.
BLCTT_A_236446 41..54

1Institute of Hematology, Ha’Emek Medical Center, Afula, Israel; 2Department of Hematology and Bone Marrow Transplantation, Rambam Health Care Campus, Haifa, Israel; 3Department of Hematology, Shaare Zedek Medical Center, Jerusalem, Israel; 4The Ruth and Bruce Rappaport Faculty of Medicine, Technion, Haifa, Israel Abstract: The isocitrate dehydrogenase enzyme, catalyzing isocitrate conversion to α-ketoglutarate (αKG) in both the cell cytoplasm and mitochondria, contributes to the production of dihydronicotinamide-adenine dinucleotide phosphate (NADPH) as a reductive potential in various cellular processes. IDH1 gene mutations are revealed in up to 20% of the patients with acute myeloid leukemia (AML). A mutant IDH enzyme, existing in the cell cytoplasm and possessing neomorphic activity, converts αKG into oncometabolite R-2-hydroxyglutarate (R-2-HG) that accumulates in high amounts in the cell and inhibits αKG-dependent enzymes, including epigenetic regulators. The resultant alteration in gene expression and blockade of differentiation ultimately lead to leukemia development. Myeloid differentiation capacity can be restored by obstruction of the mutant enzyme, inducing substantial reduction in R-2-HG levels. Ivosidenib, a potent selective inhibitor of mutant IDH1, is a differentiating agent shown to be clinically effective in newly diagnosed AML (ND-AML) and relapsed/refractory (R/R) AML harboring this mutation. The drug is approved by the Food and Drug Administration (FDA) as a single-agent treatment for R/R AML. Significance of mutated IDH1 targeting and a potential role of ivosidenib in AML management, when used either as a single agent or as part of combination therapies, will be reviewed herein.
Y-PSZ/Bioglass 45S5 composite obtained by the infiltration technique of porous pre-sintered bodies using sacrificial molding

The aim of this work was to obtain porous ceramic parts based on Zirconia stabilized with 5mol. % Yttria (5Y-PSZ), suitable for the infiltration with bioactive glasses, using 3D printed sacrificial polymeric molds. In a first step, honeycomb structured molds were designed with the SolidWorks software and manufactured by 3D printing using polylactic acid filaments (PLA). These molds were filled with a ceramic mass composed of 5Y-PSZ nanoparticles containing 3wt% polymeric binder and consolidated under pressure of 10MPa and then sintered at 1200 °C-30 min the polymeric molds were consumed. The obtained hexagonal-shaped, porous 5Y-TZP bodies were infiltrated with the bioactive glass 45S5, calcium sodium phosphosilicate, at 1350 °C. The materials were characterized by their relative density, their phase composition by X-ray diffraction analysis, and their microstructure by scanning electron microscopy (SEM-EDS), besides their mechanical properties of hardness and fracture toughness. Pre-sintered 5Y-PSZ substrates exhibit relative density around 75%, and 90% after sintering and Bioglass infiltration. The samples' microstructure is composed of a 5Y-PSZ matrix of sub-micrometric zirconia grains with an average size of 1.0 m, besides the secondary infiltrated glassy phase homogeneously distributed, with a Ca/P ratio of 1.7, close to the ideal proportion for hydroxyapatite formation. In conclusion, sacrificial molding is an interesting route to obtaining dense Y-PSZ/Bioglass 45S5 composite in a honeycomb format.
Public Goods, Uncertainty and Contingent Claims

A population of agents decides by majority rule on the realization of a discrete public good whose costs are common knowledge while its benefit is uncertain but is the same for all agents. Agents differ in their valuation of the public good, because they may have different levels of risk aversion or may differ in their expectations of the public good’s benefit. Consequently, a majority might reject a beneficial public good if its costs are shared equally. We present a financing procedure which is budget balanced, easy to implement and to understand, and is individually rational, i.e., makes ex ante all agents better off: If the public good is financed through the dispostion of claims contingent on its realized benefit, all agents will then vote for the implementation of the public good. If all agents agree on the public good’s expected benefit, only ex ante socially beneficial public goods are implemented.
Leadership and change in organization

Organizations are facing every day the need to change. Change is inevitable due to dynamic environment organizations deal with. Organizations undertake changes to survive or to be more effectiveness. Changes may be small or big, whatever they are change process needs to be managed. Organizations are interested to have successful changes and effective leadership plays an important role in organizational change success Effective leadership is always required to bring effective changes. Leaders have an important role during change management. Employees have positive attitudes and behavior to organizational change, when they see that leaders believe in proposed change and they work hard to make change process successful during organizational change, leaders have to create an environment where employees feel to be protected from change and they feel that leadership will support them during difficulties. Employees needs that their leaders to create connections and commitment during change. In this paper, we will analyze the role of leaders in change process. Also, we will describe what a visionary leader is. During change process there are different phases (Kotter, 1996). This paper will analyze what a leader can do in each phase. Also, we will distinguish the differences among managers, change agent and leaders. Key word: change agent, change process, leader, organizational change, visionary leader.
Assessing portfolio and asset returns of some financial and non- financial companies on the Ghana stock exchange using a 3-factor model

This study on the Ghana Stock Exchange (GSE), investigated, if the overall size of the market, affects the fundamentals of the Fama French 3-Factor model, and to ascertain if the Fama French model can be used effectively to assess portfolio and assets return for companies listed on the Ghana Stock Exchange. In this paper, portfolios of assets of companies on the Ghana Stock Exchange are constructed and analyzed using the Fama-French 3-factor model. The empirical data which consists of assets of 15 companies listed on the GSE, including assets of both financial and non-financial companies for good representation of the Ghana Stock Exchange. We found that the basic principle of the model is not satisfied. This is attributed to a number of factors which include overall size of the market, volume of trade, and high leverage (more debt than equity) associated with financial firms. High debt/equity ratio is linked to high risk. Keywords: Market Capitalization, Book-to-market ratio, Portfolio, Small minus big, High minus low
Analysis of PAPR Reduction techniques in OFDM System

: In the present modern wireless communication world, OFDM technique plays an important role in the transmission of multiple signals simultaneously over a single transmission path. OFDM is the good choice for multipath propagation systems. But, this multi carrier modulation technique is suffering with a PAPR problem due to the addition of number of narrow orthogonal sub-carries at OFDM transmitter. This PAPR problem leads to power inefficiency in RF section of the transmitter. To reduce this PAPR in OFDM system, numbers of techniques are proposed and implemented. In this paper we done analysis of different PAPR reduction techniques of OFDM systems and compared their PAPR values through simulation results
Analysis of Prediction Techniques

The technique through which important information is extracted from the raw data collected within the databases is known as data mining. The future scenarios related to current data can be predicted with the help of prediction analysis technique provided by data mining. The prediction analysis is the combination of clustering and classification. There are numerous techniques proposed by various researchers in order to provide prediction analysis. In this review paper, various techniques proposed by various authors are analyzed to understand latest trends in the prediction analysis.
Sports Sequence Images Based on Convolutional Neural Network

Convolution neural network has become a hot research topic in the field of computer vision because of its superior performance in image classification. Based on the above background, the purpose of this paper is to analyze sports sequence images based on convolutional neural network. In view of the low detection rate of single-frame and the complexity of multiframe detection algorithms, this paper proposes a new algorithm combining single-frame detection andmultiframe detection, so as to improve the detection rate of small targets and reduce the detection time. Based on the traditional residual network, an improved, multiscale, residual network is proposed in this paper. (e network structure enables the convolution layer to “observe” data from different scales and obtain more abundant input features. Moreover, the depth of the network is reduced, the gradient vanishing problem is effectively suppressed, and the training difficulty is reduced. Finally, the ensemble learning method of relative majority voting is used to reduce the classification error rate of the network to 3.99% on CIFAR-10, and the error rate is reduced by 3% compared with the original residual neural network.
From Silver to Platinum: The Effect of Frequent Flier Tier Levels on Airline Demand

How do customer loyalty programs create switching costs? We estimate the demand effects of tier levels within a frequent flier program by exploiting discrete tier thresholds. We have two main results. First, members increase demand to reach a higher tier level just before the end of the calendar year when tier levels are determined, but do not manipulate demand in the months before. Second, using a fuzzy regression discontinuity design with running variables from earlier months, we show that upgraded members further increase their demand to enjoy the tier level benefits. Both effects are increasing in tier level. These findings are consistent with economic theories which point out that loyalty programs aim to create convex switching costs.
The Risk-Return Relation Puzzle

Abstract A positive stock market variance-return relation is the key building block of extant rational-expectations asset pricing models. Empirical evidence is elusive despite forty years of intensive academic research. The conjecture is also resoundingly refuted by the late 1990s' dotcom bubble featured by sharp increases in both market prices and variance. Gao and Martin (2021) , Lochstoer and Muir (2021) , and Nagel and Xu (2021) interpret empirical findings as evidence of irrational expectations. Ai, Han, and Xu (2021) attribute the weak or negative risk-return relation to learning about economic fundamentals with imperfect signals. Guo, Lin, and Pai (2021) argue for two types of fundamental variance that have opposite effects on conditional equity premium and market prices. More research is needed to explain the risk-return relation puzzle prevalent in both U.S. and Asia-Pacific markets.
Volatility Estimation via First Exit Times

Estimation of volatility is important for many financial applications. The most common methods are based on a time series analysis, either sampling prices at regular intervals or using extreme values from within the time intervals. We examine an alternative, where we use the exit times from a price corridor. This method converges more quickly to the true volatility and is a natural fit for high frequency traders who continuously monitor price series.
Olonite Theory of Public Finance and Economic Growth / Development (2019) Explained

This study analyzed the Keynesian theory of public finance and economic growth and the Wagner’s Law of ever increasing state activities. The study used the secondary data from CBN 2019. The Real Gross Domestic Product formed the dependent variable and the independent variable of interest were the Capital Spending on Economic Services, and Spending of Transfers. The variables were validated by conducting the unit root test using the Augmented Dickey Fuller (ADF) and Phillips Perron Test (PP), and the correlation coefficient were determined using STATA and the Pearson Product Moment Correlation. A multiple regression model was employed for the study and was analysed using the Generalized Least Squares (GLSs) with the aid of Eviews 11 statistical program. The results of the study indicate that Capital Spending on Economic Services has a positive and significant impact on Economic Growth while Spending on Transfer has a negative and insignificant impact on Economic Growth. The study recommends the Olonite Theory of Public Finance and Economic Growth/Development [that Capital Spending on Economic Services should be maintained and increased and Spending on Transfer should be made Zero especially the non performing functions, also, the government should develop the refineries to start mass production in order to null off the negative effect of transfers (subsidy payment on oil import and price equalization)].
Where is the Intersection of Madison Avenue and Wall Street? Advertisement, Local Access to Investment Advice, and Stock Market Participation

We examine the effects of advertisement by investment advisory firms on household stock market participation. Exploiting variation in exposure to financial advertising for households along designated market area (DMA) borders, we find evidence that increased advertising by investment advisory firms leads to higher stock market participation. Importantly, the effects are concentrated in counties where the advertising firm has a physical presence. Consistent with fixed cost frictions to participation, these effects are predominantly among higher income households. We also find larger effects in counties with higher income and racial diversity - areas that are likely to have lower trust. Our results highlight the complementary nature of persuasive advertising and local access to finance for building trust in the market for investment advice.
Stress and the mental health of populations of color: Advancing our understanding of race related stressors

This study provides a summary of study on racial stress factors which may impact the wellbeing of communally stressed race-related individuals and also cultural populaces. That starts with evaluating the assessment on self-exposed parting and mental wellness. Even though the information which is segregation is the mainly observed part of mental wellness, discrimination can also affect mental wellness with most important elements and discrimination which is extremely bordered in the larger society. The main essentials for study include more purposeful consideration of stress development measures as a result of institutional racism, the evaluation of difficult understanding related to normal and synthetic all-natural emergencies, archiving and recognizing the wellness influences of aggressiveness opposite to immigrants, listing and also assessing defensive possessions, and also boosting our comprehension of the bewildering partnership amongst physiological wellness. Keywords—Race, stress and anxiety, racial discrimination, racism, emotional health, and mental
How Analytics Allowed the FCC to Save $7.3 Billion by Auctioning Underused Television Spectrum

Using an auction informed by analytics, the US Federal Communications Commission reallocated underutilized portions of the television spectrum. The revenue from this auction exceeded its cost by $7.3 billion, which went toward US deficit reduction. The author summarizes the Kiddoo et al. report on this groundbreaking work which won the 2018 INFORMS Franz Edelman Competition.
Full flowering phenology of apple tree (Malus domestica) in Pūre orchard, Latvia from 1959 to 2019

The Pūre orchard is one of the oldest apple orchards in the Baltic, where thousands of varieties of fruit trees from throughout the world are grown and tested. Over time, a huge knowledge base has been accumulated, but most of the observational data are stored in archives in paper format. We have digitized a small part of the full flowering phenological data of apple trees (Malus domestica) over the period of 1959 to 2019 for 17 varieties of apple trees, a significant step for horticulture and agricultural economics in Latvia. Climate change has led to significant changes in the phenology of apple trees as all varieties, autumn, summer and winter, have begun to flower earlier: from 2002 to 2019, on average full flowering was recorded to have taken place around 21 May, whereas for the period 1959–1967 it occurred around 27–28 May. To develop better-quality phenological predictions and to take account of the fragmentary nature of phenological data, in our study we assessed the performance of three meteorological data sets – gridded observation data from E-OBS, ERA5-Land reanalysis data and direct observations from a distant meteorological station – in simple phenological degree-day models. In the first approximation, the gridded E-OBS data set performs best in our phenological model.
The Impact of Emotion Language on International Negotiation (ELIN)

Communication between people of different linguisti c, social and cultural backgrounds is burgeoning nowadays in virtually all spheres of hum an interaction. Meanwhile, communication within domains such as diplomacy, international coo peration and military or political conflict typically fraught with the hazards of misconception a d misinterpretation needs to be maximally effective and constructive. In this conte xt, it becomes imperative to carefully elaborate languageand culture-sensitive strategie s to minimize these risks, especially with regard to the appropriate assessment and response t o aff ct, which permeates all levels of human interaction. In response to this exigency, the ELIN research pro ject, financed by the Swiss Network for International Studies (SNIS) and co-financed by the NCCR in Affective Sciences and the Centre Interfacultaire en Sciences Affectives (CISA ), aims to foster a strategic interdisciplinary collaboration between scholars from various local a nd foreign institutions and professionals from international organizations in an attempt to provid e the international community with crosscultural insight into the emotions most relevant in conflict scenarios. Four central emotion concepts were chosen for their relevance in conflic t and negotiation: ANGER, GUILT, SHAME and PRIDE. The project, both theoretical and applied, aims to produce a contrastive account of their meaning construction and verbal communication in ei ght relevant and widespread languages of the world: the 6 official languages of the UN (Engl ish, French, Spanish, Arabic, Chinese and Russian) together with German and Hebrew. In this w ay, the project seeks to enhance public awareness on cultural differences in the realm of e motional display and to contribute to the professional training and practices of professional de ling with international communication. Our multidisciplinary approach incorporates researc h methods from the affective sciences, psycholinguistics, lexical semantics, tra nslation/interpretation studies, cognitive linguistics, corpus linguistics, and critical disco urse analysis applied to three subprojects:
HFSS (HIGH-FAT, SALT, AND SUGAR) INTAKE THROUGH MEALS, SNACKS, AND BEVERAGES AMONG ADOLESCENT

This India has undergone lifestyle changes that have resulted in unhealthy eating habits, such as a high intake of HFSS (High-Fat, salt, sugar) food. Adolescents and young adults are the main groups affected and exposed to the adverse eating habits. Overweight and obesity have been significant public health issues in both developing and developed nations. India is a developing nation that is transitioning from under nutrition to obesity as a result of rapid industrialization and urbanisation. Obesity and its negative effects are a high concern in developing countries due to high fat, salt, and sugar food consumption (HFSS), unhealthy food patterns, sedentary lifestyle, lack of healthcare facilities, and financial support (i.e. diabetes, ischemic heart disease, hypertension, abdominal obesity and dyslipidaemia, etc.) Index Terms – HFSS (High-Fat, salt, sugar) Food Consumption, Dietary pattern, Adolescents.
Discovering and Achieving Goals with World Models

How can an artiﬁcial agent learn to solve a wide range of tasks in a complex visual environment in the absence of external supervision? We decompose this question into two problems, global exploration of the environment and learning to reliably reach situations found during exploration. We introduce the Explore Achieve Network (ExaNet), a uniﬁed solution to these by learning a world model from the high-dimensional images and using it to train an explorer and an achiever policy from imagined trajectories. Unlike prior methods that explore by reaching previously visited states, our explorer plans to discover unseen surprising states through foresight, which are then used as diverse targets for the achiever. After the unsupervised phase, ExaNet solves tasks speciﬁed by goal images without any additional learning. We introduce a challenging benchmark spanning across four standard robotic manipulation and locomotion domains with a total of over 40 test tasks. Our agent substantially outperforms previous approaches to unsupervised goal reaching and achieves goals that require interacting with multiple objects in sequence. Finally, to demonstrate the scalability and generality of our approach, we train a single general agent across four distinct environments. For videos, see https://sites.google. com/view/ exanet/home .