Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifikasi Bidang Gelincir Menggunakan Metode Geolistrik Tahanan Jenis Konfigurasi Dipole-Dipole Pada Lokasi Pembangunan Observatory Astronomy

An Electrical Resistivity Tomography (ERT) geoelectric survey has been carried out using a dipole-dipole configuration at the ITERA OAL construction site, Mount Betung, Lampung. Determination of the slip plane is identified using the geoelectric resistivity mapping method, where the resistivity measurement uses a resistivity meter. Data processing was performed using Res2DInv. The results of data processing refer to the results of previous studies, which take into account the lithology of the rock making up the slopes. Measurements were made on three different tracks with a length of 180 meters for each track. The resistivity value of the subsurface rock in the study area consists of 3 layers, the base layer with low resistivity ranging from 13 Ωm to 69.4 Ωm is indicated as clay, the layer between the lowest layer and the highest layer with moderate resistivity ranging from 160 Ωm to 896 Ωm is indicated as a tuff, and the topmost layer with a high resistivity value with a resistivity value greater than 1000 Ωm is indicated as a pyroclastic deposit with volcanic rock fragments. The results of data processing show that the resistivity value of the sliding field is in the range of 69.4 Ωm with a depth of 27.7 meters. The types of landslides that may occur are translation landslides.
Building Information Modeling for Existing Residential Buildings in Armenia

This article is an overview of the ways of introduction and operation of Building Information Modeling (BIM) in Industrial countries with big heritage of old multi-apartment residential buildings needing systematic and capital maintenance. Particular attention is being paid to the experience of the former Soviet States that have similar background, but different paths of development followed by the collapse of the Soviet Union. The issue is particularly critical for the Republic of Armenia that has a big heritage of residential buildings necessitating management and enhancement of seismic resilience. Six main components of the issue were introduced that are critical for the development of the institute of residential building management and may be sustained and developed by the means of information technologies and introduction of BIM.
PROSPECTIVE OF SOLAR CELL AS RENEWABLE ENERGY SOURCE

The world’s fossil fuel resources are unable to sustain our current energy requirements beyond the next few decades and so the need for inexpensive alternatives is now urgent. Organic devices are well placed to meet the needs of both the electronics and energy industries because their manufacture does not require expensive processing steps and they can be adapted to a range of applications. Consequently there has been significant interest in this fiel d over recent years and there are now many research groups world-wide investigating the semiconducting properties of conjugated materials and their use in LEDs, photovoltaic and transistors. This activity of creating electricity through the use of organic solar cells is an example of one way scientists are trying to alleviate some of the dependence on non-renewable resources. It is the purpose of my research proposal to explore that with a little human ingenuity, other ways to create energy can be
Inflation Forecasting in Nepal: A Univariate Time-Series Approach

This paper uses several standard univariate time series models and out-of-sample forecasts to assess their forecasting ability with year-on-year monthly inflation in Nepal over the period mid-August 2002 to mid-March 2021, corresponding to Nepal’s fiscal year. These include conventional models based on seasonal and monthly dummies, HoltWinters method with seasonality, standard ARIMA models, autoregressive models with different error structures and more sophisticated unobserved component model. It finds that an autoregressive model with AR(1) errors consistently outperforms its competing models based on the mean squared forecast error (MSFE) and the direction of change. The results are robust to forecast horizons, out-of-sample forecast period, different lags structures and tests of predictability. JEL Classification: C13, C22, C53, E31
Towards network optimization using Graph Neural Networks

Recent advances in Deep Reinforcement Learning have shown a significant improvement in decision-making problems. An example of the successful application is in the use of DRL to design an algorithm to allocate limited resources to different tasks in a computer cluster. Another successful example is DRL in robotics, where a robot can learn a policy to map video images to robot’s actions. These tasks, and many others from different fields, have been typically performed by the design of complex heuristics adapted to a simplification of the real problem. These heuristics are not flexible and they have difficulties to adapt to more sophisticated scenarios. DRL, on the other hand, is able to learn from past experiences and approximate its actions to scenarios never seen before. In DRL there is an agent interacting with the environment, and for each action he makes he will receive a positive or negative reward, indicating if it was a good or bad action respectively. Thus, the agent is capable to remember a similar state to the one he is facing and to pick the action that would give him a higher reward. The networking community has started to investigate how DRL can provide a new breed of solutions to relevant optimization problems. Some of these problems include to find the optimal routing given input traffic demands or network resource management. However, most of the state-of-the-art DRL-based networking techniques fail to generalize, meaning that they can only operate over network topologies seen during training. The reason behind this important limitation is that existing DRL networking solutions use standard neural networks (e.g., fully connected, convolutional neural networks, etc.), which are unable to learn graph-structured information. Computer networks are inherently represented as graphs, and thus, it’s an important aspect to learn this graph -structured information for solving network optimization problems. In
A Cross Sectional Study on Gadget Dependency Among Undergraduate Medical Students and Its Effect on Health

Gadget is defined as a transportable electronic device and has various effects due to its dependency among the undergraduates. The degree of dependence plays an important role which endangers the health and lifestyle of the students indirectly affecting both quantity and quality of being a doctor among the medical students. This study was conducted to assess the gadget dependency among medical students and its effect on health. This was a cross sectional study conducted from June 2021 to July 2021 in Manipal University College Malaysia (MUCM). An electronic survey through Google forms was distributed to the students from MBBS Sem 1 to Sem 10 and a total of 156 responses were collected. The questionnaire consisted of 3 parts including sociodemographic data, 12 questions regarding the perceived social support among the students, 27 questions on the use of the technological gadgets, gadgets dependency among participants, the effect on health of the participants and the safety measures while using gadgets. To analyse the data, statistical tests (Unpaired t test, ANOVA, correlation and simple logistic regression) were done by using Epi Info version 7.2. Findings revealed that 63.46% from 156 participants had more than 6 hours of time on gadgets. Study was the main purpose for students using gadgets (96.8%) followed by entertainment purposes (95.51%) and communication purposes (92.3%). Among 156 participants, 66.67% of them had high perceived social support. There was significant association between age, ethnicity and academic semester with gadget dependency. This study showed there was a negative, little if any correlation between perceived social support and gadget dependency. 74.4% of participants agreed that survival is difficult without technology gadgets and 83.3% of the participants agreed that IT education is mandatory for higher education. Nearly 54.5% of the participants had defective vision, 58.4% experienced physical discomfort and 59.6% felt ill and tired after long use of gadgets. Overall, the gadget dependency among students in MUCM was high but the effect on health was not significant.
MICU1 and MICU2 Play an Essential Role in Mitochondrial Ca<sup>2+</sup> Uptake, Growth, and Infectivity of the Human Pathogen <named-content content-type='genus-species'>Trypanosoma cruzi</named-content>

The mitochondrial Ca2 uptake in trypanosomatids, which belong to the eukaryotic supergroup Excavata, shares biochemical characteristics with that of animals, which, together with fungi, belong to the supergroup Opisthokonta. However, the composition of the mitochondrial calcium uniporter (MCU) complex in trypanosomatids is quite peculiar, suggesting lineage-specific adaptations. In this work, we used Trypanosoma cruzi to study the role of orthologs for mitochondrial calcium uptake 1 (MICU1) and MICU2 in mitochondrial Ca2 uptake. T. cruzi MICU1 (TcMICU1) and TcMICU2 have mitochondrial targeting signals, two canonical EF-hand calcium-binding domains, and localize to the mitochondria. Using the CRISPR/Cas9 system (i.e., clustered regularly interspaced short palindromic repeats with Cas9), we generated TcMICU1 and TcMICU2 knockout (-KO) cell lines. Ablation of either TcMICU1 or TcMICU2 showed a significantly reduced mitochondrial Ca2 uptake in permeabilized epimastigotes without dissipation of the mitochondrial membrane potential or effects on the AMP/ATP ratio or citrate synthase activity. However, none of these proteins had a gatekeeper function at low cytosolic Ca2 concentrations ([Ca2 ]cyt), as occurs with their mammalian orthologs. TcMICU1-KO and TcMICU2-KO epimastigotes had a lower growth rate and impaired oxidative metabolism, while infective trypomastigotes have a reduced capacity to invade host cells and to replicate within them as amastigotes. The findings of this work, which is the first to study the role of MICU1 and MICU2 in organisms evolutionarily distant from animals, suggest that, although these components were probably present in the last eukaryotic common ancestor (LECA), they developed different roles during evolution of different eukaryotic supergroups. The work also provides new insights into the adaptations of trypanosomatids to their particular life styles. IMPORTANCE Trypanosoma cruzi is the etiologic agent of Chagas disease and belongs to the early-branching eukaryotic supergroup Excavata. Its mitochondrial calcium uniporter (MCU) subunit shares similarity with the animal ortholog that was important to discover its encoding gene. In animal cells, the MICU1 and MICU2 proteins act as Ca2 sensors and gatekeepers of the MCU, preventing Ca2 uptake under resting conditions and favoring it at high cytosolic Ca2 concentrations ([Ca2 ]cyt). Using the CRISPR/Cas9 technique, we generated TcMICU1 and TcMICU2 knockout cell lines and showed that MICU1 and -2 do not act as gatekeepers at low [Ca2 ]cyt but are essential for normal growth, host cell invasion, and intracellular replication, revealing lineage-specific adaptations.
The Time-Varying Evolution of Inflation Risks

This paper develops a Bayesian quantile regression model with time-varying parameters (TVPs) for forecasting inflation risks. The proposed parametric methodology bridges the empirically established benefits of TVP regressions for forecasting inflation, with the ability of quantile regression to model flexibly the whole distribution of inflation. In order to make our approach accessible and empirically relevant for forecasting, we derive an efficient Gibbs sampler by transforming the state-space form of the TVP quantile regression into an equivalent high-dimensional regression form. An application of this methodology points to good forecasting performance of quantile regressions with time-varying parameters augmented with specific credit and money-based indicators for the prediction of the conditional distribution of inflation in the euro area, both in the short and longer run
Compressão de sinais ECG utilizando wavelets extráıdas dos sinais

Um método de compressão, baseado na escolha de wavelet que se adapta ao sinal a ser comprimido, é proposto neste artigo. A wavelet é escolhida computando-se os coeficientes do filtro escala que maximizam a energia do sinal no subespaço escala, uma vez que a wavelet é unicamente determinada pelo filtro escala. A principal contribuição deste artigo é formular a escolha da wavelet como um problema de otimização com um conjunto de restrições sobre os coeficientes do filtro escala. A fim de justificar a formulação proposta, uma série de experimentos, utilizando parametrizações nos coeficientes escala, foram conduzidos para mostrar que a maximização da energia resulta em boas escolhas de wavelets para compressão.
Herbal and Dietary Supplement–Drug Interactions in Patients Taking Digoxin

Many people who use prescription medication also take complementary and alternative medicines such as a vitamin, minerals, herbal products, or other botanical drugs. The mechanisms of interaction can be based on the following methods: affecting the absorption, metabolism, and disposition of other drugs. Pharmacological effects of digoxin include the increased force of myocardial contraction, decreased heart rate and the activity of the sympathetic nervous system. Digoxin is characterized by a narrow therapeutic index and is the potential drug for interacting with other drugs, herbs, and supplements. Since these interactions can cause fatal and dangerous complications; with regard to these properties, we decided to review the evidence about the interaction between herbal-dietary supplements and digoxin. We searched several sources, including MEDLINE (PubMed), Embase, CINAHL, the Cochrane Library, CISCOM databases from 1970 to 2018. Our keyboards for the search were digoxin interactions, digoxin-drug interaction, digoxin-supplement interaction, and herb-drug interaction. We reviewed the following types of articles for writing this review article: case reports, case series, original articles, and review articles. Taking together, 210 articles were obtained from databases. However, only seventy-one related articles were chosen for the preparation of this review article. We found fifty herbal products that could interact via a different mechanism with digoxin. St. John’s wort has the most documented interactions with digoxin. Some of the information on these reviews resulted from in vitro and animal studies with no clinical evidence, and others resulted from clinical evidence. Therefore, our confirmation of them in the body is incomplete. We recommend that the use of these herbs with digoxin be avoided.
High-resolution subglacial topography around Dome Fuji, Antarctica, based on ground-based radar surveys conducted over 30 years

Abstract. The retrieval of continuous ice core records of more than 1 Myr is an important challenge in palaeo-climatology. For identifying suitable sites for drilling such ice, the knowledge of the subglacial topography and englacial layering is crucial. For this purpose, extensive ground-based ice radar surveys were done over Dome Fuji in the East Antarctic plateau during the 2017–2018 and 2018–2019 austral summers by the Japanese Antarctic Research Expedition, on the basis of ground-based radar surveys conducted over the previous ~ 30 years. High-gain Yagi antennae were used to improve the antenna beam directivity and thus attain a significant decrease in hyperbolic features in the echoes from mountainous ice-bedrock interfaces. We combined the new ice thickness data with the previous ground-based data, recorded since the 1980s, to generate an accurate high-spatial-resolution (up to 0.5 km between survey lines) ice thickness map. This map revealed a complex landscape composed of networks of subglacial valleys and highlands, which sets substantial constraints for identifying possible locations for new drilling. In addition, our map was compared with a few bed maps compiled by earlier independent efforts based on airborne radar data to examine the difference in features between sets of the data.
Hierarchical Hexagon: A New Fault-Tolerant Interconnection Network for Parallel Systems

Abstract A new interconnection network topology called Hierarchical Hexagon HH(n) is proposed for massively parallel systems. The new network uses a hexagon as the primary building block and grows hierarchically. Our proposed network is shown to be superior to the star based and the hypercube networks, with respect to node degree, diameter, network cost, and fault tolerance. We thoroughly analyze different topological parameters of the proposed topology including fault tolerance routing and embedding Hamiltonian cycle.
DEPRESSION DETECTION USING MACHINE LEARNING

: Depression is a mental state in which people develop aversion to living. Depression can produce serious effects on the health of an individual, both physically and emotionally. It features sadness in extreme measures, and can often lead to suicides. Depression is a disorder of major public health importance that affects women more than men. According to a report by WHO, dated June 2019, India is the most depressed country in the world, with 6.5% of its total population being victim to depression. And to treat such an illness, the first step is identifying it. The identification process is often tedious, with no accurate result. Psychologists usually use a ‘PATIENT HEALTH QUESTIONNARIE’ to detect depression. But this method can be deceived easily if a patient wishes to answer differently. Hence, we come forward to provide an effective method to detect depression using Machine Learning. We obtain data in the form of text, from the patients/users on a regular basis. This textual data is interpreted by classification-based algorithm to detect signs of depression. The algorithm takes readings of emotion from the input text given by the user, before it finally announces if there is any depression found in the text. Classification algorithms such as K-Nearest Neighbors, Naïve Bayes, Decision Tree and Random Forest have been used for the detection model. This aids us in choosing the algorithm that provides best accuracy. Also, we continuously analyze previous readings of the user, to detect changes in the depression level. This is often represented as graphical representation that helps the user to easily identify their mood swings. Such accurate diagnosis reduces the psychologist’s work to half. The user is immediately warned of their depression level, and they are urged to get professional help. The proposed scheme not only achieves high accuracy due to its Machine Learning Approach, but also inherits scalability regarding the input size.
THE CAPSULE HOTEL AS AN INNOVATIVE FINANCIAL MANAGEMENT SYSTEM IN THE AIRPORTS: THE NEAPOLITAN CASE OF “BENBO”

The paper analyzes an innovative investment organizational model to be realized in the airport space, branded “capsule hotel”, whose mkt model directly recalls the logic of “b & b”. Objective of the reasoning is to show how, given the spread that such a model is having a global and European level, the recent implementation project of this service within the Naples airport, international airport, but medium-range could boost the attractiveness of the same and their attributes nodality. What emerges from the survey conducted, is that the city of Naples, making it a leader in the national project of such a scale, it would receive a major impact in terms of visibility and consequent increase of the tourist flow and a strong impetus to the overall development of tourism in the South.
OP-OEPJ210040 1..25

Whether economic growth improves the human lot is a matter of conditions. We focus on Japan, a country which shifted in the 1990s from a pattern of rampant economic growth and stagnant well-being, to one of modest growth and increasing well-being. We discuss concurrent policy reforms and analyse the changes in wellbeing. In particular, we assess whether the correlates of the increase in well-being are consistent with those expected from the reforms. We apply Blinder–Oaxaca decomposition to World Values Survey data. Results show that improved conditions for the elderly, parents and women, that is the primary groups targeted by the reforms, correlate with well-being increases. This evidence is consistent with the hypothesis that social safety nets can make economic growth compatible with sustained increases in well-being. JEL classifications: I31, H50, O53, O10
An effective approach to improve ethanol productivity by simultaneous saccharification and fermentation of rice straw

ABSTRACT Fuel ethanol was produced using rice straw with the simultaneous saccharification and fermentation (SSF) method. The influence of cellulose liquefaction pretreatment and Fe2+ quantity on ethanol productivity was investigated in detail. At the same time, the optimized conditions including fermentation temperature, Fe2+ amount, yeast inoculation quantity, and the inoculated cellulose enzyme dosage in the SSF process were systematically investigated by analyzing fuel ethanol yield. The result indicated that fuel ethanol yield was 0.319 g per gram rice straw by SSF approach when appropriate amount of Fe2+ was added into the reaction system. The optimal technology parameters were: fermenting temperature of 36°C, Fe2+ amount of 4 mg · g−1, inoculating proportion of 20%, cellulose enzyme of 20 IU · g−1, and Pachysolen tannophilu/saecharomyces cerevisiae of 1:2 ratio. The ethanol yield under the best conditions was larger than that of the control group. We hope that this research can facilitate to achieve large-scale comprehensive utilization for rice straw.
ANTIOXIDANT ACTIVITIES IN SELECTED VARIETIES OF RED LETTUCE (Lactuca sativa L.) EXPOSED TO WATER DEFICIT STRESS

The influence of water deficit stress on the leaf characteristic and antioxidant profile of three red lettuce varieties (Lactuca sativa L.), a commonly grown salad vegetable in the Cordillera region, was studied. The leaf area, leaf length and leaf width of the lettuce plants were reduced by medium water stress (MW) and low water stress (LW). However, significant increases in total phenolics (TP) and ascorbic acid (AA) were observed in LW-treated plants. This resulted in a 13% increase in total antioxidant capacity in Red Rapids and 8% increase for both Lollo Rosa and Falbala. Total anthocyanins, however, was not influenced by water stress imposition. Moreover, the enzymatic antioxidants (i.e., superoxide dismutase, ascorbate peroxidase and catalase) increased significantly in lettuce treated with MW and LW. Red Rapids showed the highest increase in enzymatic activity while the deep red varieties Lollo Rosa and Falbala exhibited higher increases in terms of TP and AA. This research indicates that controlled water deficit can increase TP, AA and enzymatic contents in red lettuce resulting in a higher valued crop with higher antioxidant content.