Daily Exchange Research Articles

Early Bronze Age obsidian networks: A view from Project ArAGATS

As a testimonial to Ruben Badalyan’s indelible contributions to the archaeology of the South Caucasus, this paper presents the results of a portable X-ray fluorescence study of a large sample of securely provenienced Early Bronze Age obsidian artifacts and debris from the excavations of Project ArAGATS, the collaborative program of archaeological research that we co-founded a quarter of a century ago. Statistical analyses were performed on a corpus of 467 pXRF assays of materials from the sites of Gegharot and Aragatsi Berd, located on the northeast flank of the Tsaghkahovit Plain of central Armenia. The results shed important new light on changing resource exploitation strategies over time that may be indices of variable homelands for Gegharot’s settlers. Moreover, variation in exchange networks across Gegharot’s topographically defined sectors indicate differential participation in regional exchange networks by contemporaneous households. Taken together, the results of this study indicate that the material homogeneity of Kura-Araxes villages like Gegharot need not suggest a lack of variability in daily experiences, social networks, and exchange relationships.

Criar la sal

This article describes and analyses the daily work of salt workers from the aboriginal community of San Miguel de Colorados in northwest Argentina. It intends to explore how their extraction practices involve a continuous flow of relationships with a living space, manifested through the daily exchange of energy, attachments and substances. These exchanges have a dual effect on salt work: They prevent the diseases that some beings in the environment can cause when they feel threatened and promote mineral production by transferring strength and luck. In the area under study, salt extraction and other activities conducted in (and with) the landscape are organized according to local ontology, which affirms that all things on earth are living and interrelated. In resonance with other research on the Argentine Puna and the Andes, this article aims to present an ethnographic concept of production defined by the inseparability of issues of the cosmos from ethical and political controversies and economic and material needs from the world’s vital and affective processes.

Forecasting exchange rates in Sri Lanka: a comparison of the double seasonal autoregressive integrated moving average models (DSARIMA) and SARIMA models

Exchange rates serve as a medium for currency trading in the financial market. The variations and the uncertainty movements in exchange rates have a potential effect on the performance of a country. The objective of this study is to forecast daily exchange rates in Sri Lanka using Double Seasonal Autoregressive Integrated Moving Average (DSARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) with Autoregressive Conditional Heteroscedasticity (ARCH)/ Generalized ARCH (GARCH) models. The study collected a few daily exchange rates from the Yahoo finance website in terms of LKR from 1st January 2008 to 28th February 2022. The DSARIMA and SARIMA models were incorporated with the ARCH/ GARCH specifications of normal, skew-normal, student-t and skew-t due to the accurate specification of the proper error distribution led to an increase in the accuracy of the fitted model. The model comparisons were carried out considering different performance measures. The overall results from the actual and fitted graphs and lower error values of the fitted models suggested a SARIMA model for CHF/LKR, a SARIMA model with ARCH/GARCH for USD, EURO, JPY, GBP and AUD against LKR and a DSARIMA model with ARCH/GARCH for CAD and SGD against LKR were suitable to forecast the respective exchange rate. Overall, the results from this study will support government, investors, corporate, financial and managerial sectors in their future decisions to accomplish their objectives. The originality of this study concerns the application of DSARIMA models in exchange rates due to the availability of double seasonality in data.

Impact of first-line use of caplacizumab on treatment outcomes in immune thrombotic thrombocytopenic purpura

BackgroundThe von Willebrand factor–directed nanobody caplacizumab has greatly changed the treatment of immune thrombotic thrombocytopenic purpura (iTTP) in recent years. Data from randomized controlled trials established efficacy and safety. ObjectivesThis study aims to address open questions regarding patient selection, tailoring of therapy duration, obstacles in prescribing caplacizumab in iTTP, effect on adjunct treatment, and outcomes in the real-world setting. MethodsWe report retrospective, observational cohorts of 113 iTTP episodes treated with caplacizumab and 119 historical control episodes treated without caplacizumab. We aggregated data from the caplacizumab phase II/III trials and real-world data from France, the United Kingdom, Germany, and Austria (846 episodes, 396 treated with caplacizumab, and 450 historical controls). ResultsCaplacizumab was efficacious in iTTP, independent of the timing of therapy initiation, but curtailed the time of active iTTP only when used in the first-line therapy within 72 hours after diagnosis and until at least partial ADAMTS13-activity remission. Aggregated data from multiple study populations showed that caplacizumab use resulted in significant absolute risk reduction of 2.87% for iTTP-related mortality (number needed to treat 35) and a relative risk reduction of 59%. ConclusionCaplacizumab should be used in first line and until ADAMTS13-remission, lowers iTTP-related mortality and refractoriness, and decreases the number of daily plasma exchange and hospital stay. This trial is registered at www.clinicaltrials.gov as #NCT04985318.

A New Viterbi-Based Decoding Strategy for Market Risk Tracking: an Application to the Tunisian Foreign Debt Portfolio During 2010–2012

In this paper, a novel market risk tracking and prediction strategy is introduced. Our approach takes volatility clustering into account and allows for the possibility of regime shifts in the intra-portfolio's latent correlation structure. The proposed specification combines hidden Markov models (HMM) with latent factor models that takes into account the presence of both the conditional skewness and leverage effects in stock returns. A computationally efficient expectation-maximization (EM) algorithm based on the Viterbi decoder is developed to estimate the model parameters. Using daily exchange rate data of the Tunisian dinar versus the currencies of the main Tunisian government's creditors, during the 2011 revolution period, the model parameters are estimated. Then, the suitable model is used in conjunction with a Monte Carlo simulation strategy to predict the Value-at-Risk (VaR) of the Tunisian government's foreign debt portfolio. The backtesting results indicate that the new approach appears to give a good fit to the data and can improve the VaR predictions, particularly during financial instability periods.

Evaluation of carbon balance and carbohydrate reserves from forced (Vitis vinifera L.) cv. Tempranillo vines.

Elevated temperatures during berry ripening have been shown to affect grape quality. The crop forcing technique (summer pruning that 'force' the vine to start a new cycle) has been shown to improve berry quality by delaying the harvest date. However, yield is typically reduced on forced vines, which is attributed to vine low carbon availability soon after forcing and likely incomplete inflorescence formation. The present study aims to estimate the carbon balance of forced vines and evaluate vine responses to changes in carbon patterns due to forcing. Three treatments were studied on Tempranillo cultivar: non-forced vines (Control), vines forced shortly after fruit set (CFearly) and vines forced one month later at the beginning of bunch closure (CFlate). Whole canopy net carbon exchange was modelled and validated using two whole canopy gas exchange chambers. In addition, non-structural carbohydrate reserves at budburst, forcing date and harvest, were analysed. Yield, yield components and vegetative growth were also evaluated. Harvest date was delayed by one and two months in the CFearly and CFlate, respectively, which increased must acidity. However, yield was lower in the forced treatments compared to the Control (49% lower for CFearly and 82% for CFlate). In the second year, at the time when CFearly and CFlate dormant buds were unlocked (forced budburst), forced vines had significantly lower non-structural carbohydrates than Control vines at budburst. Although the time elapsed from budburst to reach maximum net carbon exchange was longer for the Control treatment (80 days) than for the forced treatments (about 40 days), average daily net carbon exchange until harvest was comparable between Control (60.9 g CO2/vine/day) and CFearly (55.9 g CO2/vine/day), but not for CFlate (38.7 g CO2/vine/day). In addition, the time elapsed from budburst to harvest was shorter in forced treatments (about 124 days) than for the Control (172 days). As a result, the cumulative net carbon exchange until harvest was reduced by 35% (CFearly) and 55% (CFlate) in the forced treatments. However, no differences in carbon reserves at harvest were observed between treatments partly helped by the higher source:sink ratio observed in forced than Control vines.

Exploring the multimodal role of Cnicus benedictus extract in the modulation of growth, hematobiochemical, histopathological, antioxidative performance, and immune-related gene expression of Oreochromis niloticus challenged with Aeromonas hydrophila

This study explored the growth efficiency and the intracellular pathways by which Cnicus benedictus extract (CBE) acts. It investigated the antioxidant effects and efficacy of CBE as a fish supplement in attenuation of Aeromonas hydrophila in Oreochromis niloticus fish. Mono-sex Nile tilapia fish (n = 225) were randomly allocated to five groups in triplicate aquaria (n = 3 tanks per group, 15 fish per tank, with 120 L of water per tank) with a daily water exchange rate of 20%. After adaption for 2 weeks and body weight measuring, the experimental groups were fed isonitrogenous and isocaloric diets with different dosages of the ethanolic extract of C. benedictus for 10 weeks. The five groups were identified as the control group (CBE0.0), which was fed on the basal diet, while the second (CBE0.1), the third (CBE0.2), the fourth (CBE0.4), and the fifth (CBE0.6) groups were fed the basal diet supplemented with 0.1%, 0.2%, 0.4%, and 0.6% of C. benedictus extract, respectively. After the 10-week feeding trial was completed, the fish were inoculated with the PCR-identified pathogenic A. hydrophila in a challenge trial which lasted 15 days. A. hydrophila, one of the septicemic bacteria, causes severe economic losses, high mortality rates, and hemorrhages in Nile tilapia and other cultured freshwater fishes worldwide. The CBE was found to significantly increase the body mass, weight gain, and the specific growth rate, as well as the protein efficiency ratio of the fish. Increased survival percentage, accompanied by post challenge lymphocytosis with decreased liver enzyme levels, increased total protein, and improved kidney function markers were also seen. Additionally, CBE supplementation showed significant increases in phagocytic activity, phagocytic index, and lysosomal activity post challenge, accompanied by increases in antioxidant activity and the mRNA expression of cytokines genes hsp70 and tlr7 mRNA. The desirable effects of CBE treatment were confirmed by a histopathological examination of the height of intestinal villi and enterocytes lining the middle intestine and increases in the size of liver cells. We conclude that CBE increases the growth performance and modulates the antioxidant, inflammatory, stress, and immune-related genes in Nile tilapia. Moreover, the dietary inclusion of 0.42–0.47% CBE showed a better protective effect with the A. hydrophila challenge.

A multi-perspective input selection strategy for daily net ecosystem exchange predictions based on machine learning methods

A multi-perspective input selection strategy for daily net ecosystem exchange predictions based on machine learning methods

GenBank 2023 update.

GenBank® (https://www.ncbi.nlm.nih.gov/genbank/) is a comprehensive, public database that contains 19.6 trillion base pairs from over 2.9 billion nucleotide sequences for 504 000 formally described species. Daily data exchange with the European Nucleotide Archive (ENA) and the DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. Recent updates include resources for data from the SARS-CoV-2 virus, NCBI Datasets, BLAST ClusteredNR, the Submission Portal, table2asn, a Foreign Contamination Screening tooland BioSample.

Application of ARIMA Model in Forecasting Exchange Rate: Evidence from Bangladesh

This paper attempts to apply the ARIMA time series model to forecast the exchange rate of seven currencies (United States Dollar, Euro, Pound sterling, Australian Dollar, Japanese Yen, Canadian Dollar and Swedish Krona) in terms of Bangladeshi Taka (BDT) and to investigate the accuracy of the model by comparing the forecasted rates with the actual exchange rates. It considered daily currency exchange rates (244 selling price) of seven currencies for twelve months from January 2018 to December 2018 to forecast the subsequent one month (25 selling rate) in January 2019 rate. The Durbin-Watson test result shows an autocorrelation in the daily foreign currency exchange rate with the previous rate. The Augmented Dickey-Fuller test result shows data have unit roots and non-stationary. But the 1st differencing becomes data stationary to apply d equal to 1 in ARIMA model. Also, autocorrelation function considers MA(0) and partial autocorrelation function considers AR(1) for the ARIMA model. So, ARIMA (1,1,0) models are selected based on Ljung-Box test, root mean square error, mean absolute percent error, mean absolute error and R-square values. By using the above ARIMA models, forecasted foreign currency exchange rates next one month calculated and compared with the respective actual rates, which validate with Chi-Square test, mean absolute percent error, mean square error, root mean square error values of Goodness fit test. The result shows that predicted foreign currency exchange rates follow ARIMA (1,1,0) model, which may be applied to forecast the foreign currency exchange rates in Bangladesh.

The Impact of Fluctuating USD/RMB Exchange Rate on the Yields and Volatility of Chinese Concept Stocks

The currency exchange market plays a critical role in international trade, but it has fluctuated more frequently since the trade conflict between the U.S. and China. By collecting the daily exchange rate of the U.S. dollar (USD) against the Chinese yuan (RMB) and the NASDAQ OMX China Technology index (CHXN9000) from September 25, 2017, to January 25, 2020, this paper empirically analyzes the dynamic response of the Chinese Concept stock yields to RMB’s exchange rate changes using VAR and ARMA-GARCH models4. The results of the study show that (1) the increasing exchange rate yields of USD to RMB (depreciation of RMB) and the Chinses concept stock yields are negatively correlated in the short term; (2) Chinses concept stock returns respond significantly to the exchange rate volatility, but this effect gradually disappears after the fourth period. These findings may serve as instructive aid to investors in choosing their portfolios while facing exchange rate fluctuations.

Thermomechanical Behaviors of an Energy Pile–Raft Foundation under Intermittent Operation with Forced Heat Recharge

This paper presents an experimental investigation of the thermal and mechanical behaviors of an energy pile–raft foundation under intermittent heating operation with forced heat recharge, with 16 h of pile cooling and 8 h of forced heat recharge (referred to as 16F, where F indicates forced). The forced heat recharge was found to increase the daily heat exchange rate to 180 W/m, which was 50% higher than the value under general intermittent heating operation without forced heat recharge. The raft and building load at the pile head imposed a significant restraint on the upper part of the energy pile, leading to a minimum degrees of freedom (0.27) near the pile head. The mechanical behaviors of the pile, including strains, stresses, and pile end displacements and stresses, followed reversible paths when plotted against the daily temperature cycles. A slight residual pressure stress (10 kPa) was observed at the bottom of the raft during the initial thermal cycles.

The in-vitro effect of gonadotropins’ type and combination on Granulosa cells gene expressions

ObjectiveNowadays, different modes and timing of GnRH-agonist combined with hCG trigger, for final follicular maturation, have been described. While LH + FSH are the naturally occurring final follicular maturation trigger, hCG is commonly use during stimulated cycle, and recently the introduction of the Dual/Double trigger combines LH + FSH + hCG. In the present study we aim to investigate the messenger RNA (mRNA) expression of reproduction-related genes in human granulosa cells (GCs) exposed to the aforementioned different types and combinations of gonadotropins.Material and methodsMural GCs were obtained from follicular fluid aspirated during IVF protocol. GCs were seeded in culture for 4 days with daily medium exchange followed by administration of either hCG (1 U/ml); FSH (1 U/ml) and LH (8 U/ml); or hCG (1 U/ml) and FSH (1 U/ml) and LH (8 U/ml) for 16 h. mRNA was purified from harvested GCs and gene expression was quantitative by qPCR.Main outcome measuresThe expression of genes related to steroidogenesis (StAR/ CYP19) and oocyte maturation (COX2/Amphiregulin) in cultured GCs.ResultsThe Dual/Double trigger (LH + FSH + hCG) showed higher activation of steroidogenesis (StAR/CYP19) and maturation (COX2/Amphiregulin) as compared to the naturally occurring trigger (LH + FSH) and the hCG triggers. Moreover, while the naturally occurring trigger (LH + FSH) activated maturation significantly and more intensely than the hCG trigger, no in between group differences were observed with regards to steroidogenic related genes.ConclusionsOur findings are in agreement with clinical experience, demonstrating the superiority of the double/dual (LH + FSH + hCG) trigger over the naturally occurring and the hCG triggers.

Pengaruh COVID-19, Nilai Kurs dan Efek Bulan Ramadan terhadap Pengembalian Pasar Saham

This study aims to examine the effect of COVID-19, exchange rate and Ramadan month effect on stock market returns in consumer goods industry firm listed on the Indonesia Stock Exchange (IDX) in 2020. The sampling method used in this study is purposive sampling with predetermined criteria. The result of this study shows that COVID-19 that is proxied by daily death case, exchange rate and Ramadan month effect have no effect on stock market returns. COVID-19 that is proxied by daily recovered case have positive effect on stock market returns.

Distinct dynamics of Vibrio parahaemolyticus populations in two farming models.

Despite the recent prosperity of shrimp cultivation in China, very little is known about how different shrimp farming models influence the dynamics of Vibrio parahaemolyticus populations and the antibiotic resistance of this bacterium. To this end, we conducted continuous surveillance of V. parahaemolyticus on four farms over 3years: two traditional shrimp farms with daily water exchange and two farms operated in the recirculating aquaculture systems (RAS). No antibiotics were used in these farms to exclude the potential impacts of antibiotics on the emergence of antibacterial resistance. Multilocus sequence typing was utilized to characterize the dynamics of V. parahaemolyticus populations. Whole-genome sequencing (WGS) was conducted to determine the representative sequence types (STs) at each farm. Results revealed that the population structure of V. parahaemolyticus remained stable over time in both RAS farms, with only nine and four STs observed at each. In contrast, annual replacement of V. parahaemolyticus populations was observed in traditional farms with 26 and 28 STs identified in rearing water. WGS of 50 isolates divided them into five clusters, of which ST917a isolates harboured a genomic island that disrupted the gene recA. Pair-wised genomic comparison of isolates from the same STs showed that they were genetically related but belonged to different clones associated with geographical distribution. These results suggested that RAS presented a specific ecological niche by minimizing the water exchanges with the external environment. In contrast, traditional farming might pose a food safety issue by introducing new V. parahaemolyticus populations with antibiotic resistance genes. Our results expose the potential food safety issue associated with conventional agriculture and should encourage the development of preventive strategies to reduce the emergence of resistant V. parahaemolyticus populations.

Rapid nutrient depletion to below the physiological range by cancer cells cultured in Plasmax.

Mammalian cell culture is a fundamental tool used to study living cells. Presently, the standard protocol for performing cell culture involves the use of commercial media that contain an excess of nutrients. Although this reduces the likelihood of cell starvation, it creates nonphysiologic culture conditions that have been shown to "re-wire" cellular metabolism. Recently, researchers have developed new media like Plasmax, formulated to approximate the nutrient composition of human blood plasma. Although this represents an improvement in cell culture practice, physiologic media may be vulnerable to nutrient depletion. In this study, we directly addressed this concern by measuring the rates of glucose and amino acid depletion from Plasmax in several cancer cell lines (PC-3, LNCaP, MCF-7, and SH-SY5Y) over 48 h. In all cell lines, depletion of glucose from Plasmax was rapid such that, by 48 h, cells were hypoglycemic (<2 mM glucose). Most amino acids were similarly rapidly depleted to subphysiological levels by 48 h. In contrast, glucose and most amino acids remained within the physiological range at 24 h. When the experiment was done at physiological oxygen (5%) versus standard (18%) with LNCaP cells, no effect on glucose or amino acid consumption was observed. Using RNA sequencing, we show that this nutrient depletion is associated with enrichment of starvation responses, apoptotic signaling, and endoplasmic reticulum stress. A shift from glycolytic metabolism to mitochondrial respiration at 5% O2 was also measured using Seahorse analysis. Taken together, these results exemplify the metabolic considerations for Plasmax, highlighting that cell culture in Plasmax requires daily media exchange.

Stock Market Index Prediction Using Artificial Neural Network

Often, nonlinearity exists in the financial markets while Artificial Neural Network (ANN) could be used to expect equity market returns for the next years. ANN has been improved its ability to forecast the daily stock exchange rate and to investigate several feeds using the back propagation algorithm. The proposed research utilized five neural network models, Elman network, Multilayer Perceptron (MLP) network, Elman network with Self-Optimizing Map (SOM), MLP with SOM filter and simple linear regression, for estimating new values. Results were examined to investigate the predicting ability and to provide an effective feeds for future values. The result of the proposed simulation showed that SOM could greatly improve the convergence of the neuron networks; whereas Elman network did a better performance to capture the temporal pattern of the symbolic streams generated by SOM.A benchmark of linear regression model was also employed to show the ability of neural network models to generate higher accuracy in forecasting financial market index.

Contagion effects in ASEAN-5 exchange rates during the Covid-19 pandemic

The aim of this study is to examine the pure and fundamentals-based contagion effects in ASEAN-5 exchange rates during Covid-19 period using daily exchange rates from June 2019 to December 2020. We adopt VECM within the structural VAR framework and higher time–frequency wavelet analysis. The VECM findings show that ASEAN-5 exchange rates are cointegrated during this pandemic and should there be any disequilibrium, daily rate of adjustments in the Indonesian rupiah, Malaysian ringgit and Singapore dollar are 6.58%, 1.47% and 2.45% respectively. The wavelet power spectrum implies that Indonesia, Malaysia and Singapore experience prolonged high degree of exchange rates volatility, Thailand experiences mild volatility in the short run and high volatility in the long run and only Philippines experiences mild volatility in the short run and no heightened long run volatility. The wavelet coherence shows Indonesian rupiah reacts first to the Covid-19 shock leading to fundamentals- based contagion to Malaysia and Thailand, and temporary pure contagion based on sentimental to Philippines and Singapore. Only the Philippine peso that insulates itself from the long run shocks. These findings are important as it gives insights into the nature of contagion among ASEAN-5 exchange rates due to global shock of Covid-19 and the need for timely intervention to prevent the short run contagion turning into the long run.

The calculation of flushing time for the upper Pasur River Estuary, Bangladesh

Estimation of estuarine flushing time, a time required to transport of pollutants or any other properties from estuaries to the coast, is very important for its resource management. In this study, we estimated flushing time (T) of the upper Pasur River Estuary (UPRE) for understanding the water quality condition in the dry and wet seasons. High-resolution salinity data were collected from the PRE at high water in the dry and wet seasons in 2014 and 2019. Flushing time was calculated using the freshwater fraction method (FFM) as well as e-folding flushing time scales was estimated empirically using the salinity (non-reactive conservative) and monthly river discharge data. System flushing during the dry season was thirteen times weaker than flushing during the wet season owing to decreasing river discharge by nearly 94%. In addition, the daily exchange volume was decreased by eight times during the dry season than during the wet season. As a consequence, the conditions of the UPRE are more dynamic during the wet season due to receiving huge amount of river discharge. During the dry season, only the e-folding time scales showed higher values in the salinity maximum zone (salt plug area). This implied that the e-folding time scale is an empirical approach and was able to encompass the tidal dispersion process whereas the FFM was unable to include that process. As the PRE is a macrotidal estuary, the tide assists to flush dissolved substances from the UPRE to the coast during the dry season having negligible river discharge. In addition, there was no significant variation in water quality parameter between the salt plug area (SP) and downstream of salt plug area (DSP) during the dry season. In order to have more accuracy, a three-dimensional hydrodynamic model would be useful to compute estuarine time scales precisely.

The Impact of Macroeconomic Sustainability on Exchange Rate: Hybrid Machine-Learning Approach

This paper constructed a robust methodology to investigate the impact of news regarding macroeconomic policies on exchange rate fluctuations, and to examined the applicability of qualitative information alongside historical data to predict exchange rates. To do so, hybrid machine learning algorithms comprised of natural language processing, fuzzy logic, and support vector regression have been constructed. This study emphasizes the significance of qualitative information on investors’ subjective consideration, the decision-making process, and causality on exchange rate volatility. To perceive the causality of expected and unexpected macroeconomic news on exchange rate fluctuations, news regarding the inflation rate, interest rate, unemployment rate, balance of trade, and credit ratings has been extracted from the web. Learning automata has been adopted to construct a unique lexicon for textual analysis. Subjective considerations of decision makers based on news have been evaluated by processing using the prospect theory and composing fuzzy antecedents for the fuzzy logic phase. The fuzzy logic method attained the correlation value between the macroeconomic news and the exchange rate. Finally, support vector regression predicted the exchange rate on a daily basis. The statistical test results indicated a strong correlation between recently published macroeconomic news on daily exchange rate fluctuations and their usability for predicting exchange rates in the short term, while emphasizing the significance of sustainable macroeconomic policies on exchange rate stability.