Miracle-dz/UniFAR-FTUs huggingface dataset:
Water ortho-to-para ratio in the coma of comet 67P/Churyumov-Gerasimenko

Abundance ratios of the nuclear-spin isomers of H$_2$O and NH$_3$ have been measured in about two dozen comets, with a mean value corresponding to a nuclear-spin temperature of $\sim$ 30 K. The real meaning of these unequilibrated nuclear-spin abundance ratios is still debated. However, an equilibrated water ortho-to-para ratio (OPR) of 3 is also commonly observed. The H channel of VIRTIS (VIRTIS-H) on board Rosetta provided high-resolution 2.5--2.9 $\mu$m spectra of H$_2$O vapour in the coma of comet 67P/Churyumov-Gerasimenko (67P), which are suitable for the determination of the OPR of water in this comet. A large dataset of VIRTIS-H spectra obtained in limb-sounding viewing geometry was analysed, covering heliocentric distances from 1.24 to 2.73 au and altitudes from a few hundred metres to $>$ 100 km. The OPR, together with the H$_2$O rotational temperature and column density, were derived for each spectra. The weak lines of the $\nu_1$, $\nu_1+\nu_3-\nu_1$ and $\nu_2+\nu_3-\nu_2$ bands in the 2.774--2.910 $\mu$m range were used to calculate by how much the strong $\nu_3$ band centred at 2.67 $\mu$m is attenuated due to optical depth effects, expressed by the attenuation factor $f_{\rm atten}$. Most OPR determinations are strongly affected by opacity effects, as demonstrated by the observed anti-correlation between the OPR and the column density, and the correlation between the OPR and attenuation factor $f_{\rm atten}$. Based on both radiative transfer calculations and OPR values obtained in low-opacity conditions, we derive an OPR of 2.94 $\pm$ 0.06 for comet 67P. The water OPR measured in the coma of 67P is consistent with laboratory experiments showing that water vapour that has thermally desorbed from water ice has a statistical value of 3, regardless of the past formation process of water ice.
Effect of Feeding Different Levels of Corn Silage on Milk Yield and Quality in Dairy Assaf Ewes

This study aimed to investigate the impact of feeding by different corn silage (CS) proportions on ewes milk yield and fatty acids composition. Twenty-one lactating Assaf ewes were divided into 3 groups (7 ewes each). The following dietary treatments based on increasing the proportion of CS in the total mixed ratio (TMR) were tested; (1) 47 % AH (0 % CS in the TMR) correspond to 0 % CS, (2) 23.5 % AH (23.5 % CS in the TMR) correspond to 50 % CS, and (3) 0 % AH (47 % CS in the TMR) correspond to 100 % CS. After 8 weeks of feeding, the type of diet had no significant effect on milk yield and solid; however, it significantly affects the milk fat. The levels of C8:0 and C14:0 were not affected by different silage levels. While the C10:0 and C12:0 significantly increased when fed on a 100 % CS diet. However, a significantly lower level of C16:0 (33.22 %) was observed in the 100 % CS compared to feeding on silage at 50 and 0 % (40.66 and 37.98 %, respectively). Similar trend was observed for C18:0, the lowest was in 100 % CS compared with the different feeding diets (7.52, 12.69, 10.61 % for 100, 50, 0 %, respectively). Total USFA in milk were decreased (p < 0.05) by feeding 100 and 50 % CS compared to 0 % CS feeding. It can be concluded that the replacement of alfalfa with CS had some influence on milk composition, especially the fatty acids profile. HIGHLIGHTS Utilization of nonconventional feed ingredients is important to reduced feed cost and improving its nutritive value Milk composition, especially the fatty acids profile when replaced portions of alfalfa can be affected by feeding corn silage More research is needed to confirm our findings
Effects of Combination Treatment in Hypertensive Patients with Depression: A Systematic Review and Meta-Analysis of 27 Randomized Controlled Trials

Background Hypertension commonly co-exists with depression and is associated with adverse health outcomes. This meta-analysis aimed to examine whether combination treatment can improve the outcomes of patients with comorbid hypertension and depression. Methods We searched for relevant randomized controlled trials (RCTs) published through July 2021 using PubMed, Web of Science, China National Knowledge Infrastructure, and Wanfang Data. RCTs on patients with an antihypertensive outcome and data on mean blood pressure differences were extracted for both intervention and control groups. Continuous and dichotomous measures of outcomes were pooled using weighted mean differences (WMD) and risk ratios (RR) with 95% confidence intervals (CI) by random or fixed effects. Subgroup and meta-regression analyses were performed to identify any existing heterogeneous sources. Results A total of 27 RCTs with 2606 participants were included. Combination treatment significantly improved systolic blood pressure (SBP) by 11.27 mmHg (WMD = −11.27, 95% CI: −14.12 to −8.43), I2 = 95.4%), diastolic blood pressure (DBP) by 8.21 mmHg (WMD = −8.21, 95% CI: −10.73 to −5.69), I2 = 96.9%), and antihypertensive efficiency by 42% (RR = 1.42, 95% CI: 1.32 to 1.52, I2 = 0.0%) compared with in the control group. Combination treatment improved SBP and DBP levels in patients aged <65 years compared with those in patients aged ≥65 years (p = 0.020 and 0.007, respectively). Conclusion Pooled evidence suggests that combination treatment significantly improves both blood pressure levels and antihypertensive efficiency in hypertensive patients with depression. Elderly patients with comorbid hypertension and depression may require a more collaborative approach to improve their outcome. Registration PROSPERO registration number CRD42020213430. Registered on November 08, 2020.
Insights into Surface Ion-imprinted Materials for Heavy Metal Ion Treatment: Challenges and Opportunities

ABSTRACT Surface ion-imprinting technology (SIIT) is a novel and effective alternative to conventional methods of preparing ion-imprinted polymers. SIIT involves the coating of support materials with a polymeric layer that selectively binds with imprinted metal ions, particularly heavy metal ions. Given its specificity, predictability, and stability, SIIT has been quickly adopted in ion detection, separation, enrichment, and sensing. Here, building on the latest advances in this emerging new technology, we carried out a systematic review to summarize the 1) principles and basic components of surface ion-imprinted polymers (SIIPs); 2) preparations, properties, advantages, and disadvantages of three types of SIIP supporting materials, including inorganic (minerals, carbonaceous materials, metal oxides), organic, and composite (organic/organic, organic/inorganic, inorganic/inorganic) supports; 3) current applications of SIIT, and 4) future challenges and opportunities related to SIIT. Finally, perspectives and future research are discussed to address the pressing need for the development of SIIT for heavy metal ion treatment.
The importance of computing intermodal roundtrips in multimodal guidance systems

Most of the current intermodal traveller information applications still consider one-way journeys only. For the calculation of a roundtrip two simple one-way trips are taken into account. However, most of the journeys do not consist of simple one-way trips, as a traveller usually returns to the starting point (home, office for business trips, etc.). Also, arc cost – travel time in general – tend to be time dependent, which means that the cost of the optimum roundtrip is not necessarily the double of the cost of the optimum one-way trip. The diverse arc cost values can be based on dynamic and/or historic data. A lot of effort is spent in order to obtain and store this type of data, which is necessary for describing real-time traffic states and to make forecasts. So the next step is to make better use of this data by integrating them into the calculation of trips that take place in the future. A multimodal information service usually works as follows: The traveller indicates his starting point, his destination and the desired time of departure or arrival. The system then computes the optimum trips for private modes (car, bicycle, etc.) and public transport (all modes). It is up to the user to compare the different possibilities and to decide which one to take. Dynamic data are integrated where available. The possibility of switching between different transportation modes during the trip is rarely offered. The main reasons are the difference in the models (different graphic levels are used for different modes) and the different parameters for describing the arc cost for the different modes. Roundtrips can usually be computed for certain modes, especially for public transport, which relies on static timetable data. In this case, the intermodality is limited to some or several public transport modes of a certain region. More and more service providers offer the possibility to optimise a door-to-door trip, taking into account the time necessary to reach the first transport mode used, as well as the time to reach the destination from the last stop. This paper describes the importance of computing entire intermodal roundtrips rather than two one-way trips, as arc cost tend to vary depending on different parameters (time of the day, special events, etc.). Having more and more dynamic and historic data at hand, it should be used to the maximum possible, in order to optimise mobility habits. Computing intermodal roundtrips also means taking into account several constraints that may arise on the way, like the dependence on a certain mode or leaving behind a private vehicle at certain nodes of the network. The main constraints are pointed out, along with their importance for the calculation.
Structural based investigation of novel pyrazole-thiazole Hybrids as dual CDK-1 and CDK-2 inhibitors for cancer chemotherapy

ABSTRACT CDK-1 and CDK-2 are two promising targets for cancer treatment as they are vital in tumor development, proliferation, and apoptosis during the cell cycle process. In treating cancers, CDK inhibitors (small molecules) are used to prevent the overproliferation and overexpression of cancer cells. Consequently, inhibiting CDKs is a promising treatment strategy in oncology. The limitations imposed by current CDK-1 and CDK-2 inhibitors, including neurotoxicity and the development of resistance, have prompted our group to use the novel synthesized pyrazole-thiazole hybrid analogues to investigate their possible potency against CDK-1 and CDK-2. The research study employed detailed computational approaches including molecular docking, molecular dynamics (MD) simulations, post-MD analyses such as RMSD, RMSF, RoG, per-residue energy decomposition, hydrogen bond lifetime analysis, and drug-likeness studies like ADME properties prediction and cytotoxicity, to predict the properties and inhibitory potentials of synthesized pyrazole-thiazole hybrid analogues against CDK-1 and CDK-2. The in silico binding free energy and other analysis reported in the study revealed that four (7 g, 8a, 8b, and 8 h) of the tested molecules against CDK-1 demonstrated a higher binding affinity and structural influence on the target protein than the known inhibitor, Roscovitine (RVT). Similarly, in the case of CDK-2, four (7b, 8a, 8b, and 8f) of the tested compounds showed better results than (RVT). Furthermore, structural examination of the two proteins after binding to the inhibitors revealed that the compounds form stable complexes with the targets and significantly reduced the structural flexibility of the proteins. Therefore, this study suggests the novel pyrazole-thiazole hybrid analogues as potential CDK-1 and CDK-2 inhibitors and could be potential lead compounds for target-based anticancer drugs inhibiting the important proteins, CDK-1 and CDK-2. GRAPHICAL ABSTRACT
Devising a procedure to forecast the level of chemical damage to the atmosphere during active deposition of dangerous gases

This paper reports a procedure devised to forecast the level of chemical pollution of the atmosphere, which includes a mathematical model for the distribution of the concentration of dangerous gas in the atmosphere at its active deposition by dispersed jets of liquid, as well as a technique for its implementation. Based on the differential equations of gas distribution in space, a phased model of the propagation of a cloud of a dangerous chemical substance was built. The model describes stages in the discharge of a dangerous gaseous substance from emergency technological equipment, the deposition of dangerous gas by a finely-dispersed flow, and free propagation of the cloud in the air. The reported mathematical model makes it possible to calculate the size of pollution zones while determining the boundary safety conditions. When forecasting, the main meteorological parameters, the width of the deposition zone, and the chemical properties of both the gas and liquid are taken into consideration. The comparative analysis of the results of forecasting a conditional zone of chemical damage with the free propagation of the cloud, and at the active deposition by precipitation or technical devices, was carried out. The simulation results revealed that with an increase in the wind speed from 1 m/s to 5 m/s, the size of the affected area increases by 2.7 times, while the concentration of dangerous gas in the cloud falls by 2.5‒3 times. An algorithm has been proposed for integrating the devised methodology of forecasting the level of chemical pollution of the atmosphere into a general cycle of emergency management. It should be especially noted that the devised procedure contains the entire range of components that are necessary for its practical application. It includes a description of the procedure and practical recommendations for the use of the proposed technique in the elimination of emergencies, as well as a list of probable events when the use of the developed procedure would be most effective.
UDC 616-006.04 GPR161 RECEPTOR AS A NOVEL TARGET FOR ANTIBODY-BASED IMMUNOTHERAPY OF TRIPLE-NEGATIVE BREAST CANCER

Triple-negative breast cancer is a rare type of breast cancer, accounting for 20% of all women diagnosed with the adenocarcinoma. Triple-negative breast cancer cells are mainly characterized by the absence of estrogen receptors, progesterone receptors, and human epidermal growth factor receptors. Moreover, these cells do not respond to hormonal and targeted treatment with monoclonal antibodies. A literature review revealed several receptors in the oncogenic cells of this phenotype with potential to serve as a novel target for therapy. In particular, the G-protein coupled receptor (GPR) 161 was found to be overexpressed in triple-negative breast cancer cells, and correlated with a poor prognosis of the disease. In addition, overexpression of GPR161 in human mammary epithelial cells resulted in increased cell proliferation, migration, intracellular accumulation of E-cadherin, and the formation of multiple structures in a three-dimensional cell culture. Activation of the receptor reduces the phosphorylation of GTPaseactivating protein 1 proteins, thereby enhancing mammalian target of rapamycin signaling pathways. GPCRs belong to a family of cell membrane proteins that transform extracellular signals into intracellular signaling pathways. These receptors play a key role in many important physiological processes whose malfunction may lead to various diseases, including cancer. Several currently produced drugs target different members of the GPCR family and have shown excellent therapeutic advantages. Therefore, huge efforts are focused on developing new drugs based on GPCRs, particularly for the treatment of cancer. This article provides an overview of data that show great promise in new opportunities for the treatment of triple-negative breast cancer. In particular, research on GPCRs is highlighted as promising targets for monoclonal antibodies and, after humanization, as therapeutic drugs
Spectrograms of ship wakes: identifying linear and nonlinear wave signals

A spectrogram is a useful way of using short-time discrete Fourier transforms to visualise surface height measurements taken of ship wakes in real-world conditions. For a steadily moving ship that leaves behind small-amplitude waves, the spectrogram is known to have two clear linear components, a sliding-frequency mode caused by the divergent waves and a constant-frequency mode for the transverse waves. However, recent observations of high-speed ferry data have identified additional components of the spectrograms that are not yet explained. We use computer simulations of linear and nonlinear ship wave patterns and apply time–frequency analysis to generate spectrograms for an idealised ship. We clarify the role of the linear dispersion relation and ship speed on the two linear components. We use a simple weakly nonlinear theory to identify higher-order effects in a spectrogram and, while the high-speed ferry data are very noisy, we propose that certain additional features in the experimental data are caused by nonlinearity. Finally, we provide a possible explanation for a further discrepancy between the high-speed ferry spectrograms and linear theory by accounting for ship acceleration.
Conceiving a systemic approach to implement solar energy technology: the case of Israel

Population growth, lifestyle and income changes as well as urbanisation are powerful driving forces behind increasing demand for energy. Since 1900, world population has more than quadrupled, real income has grown by a factor of 25, and primary energy consumption has risen by a factor of 22.5. The joint phenomenon of urban and economic growth is particularly relevant in Israel where 76% of the population lives in cities and Israel economic growth rate stood at 5.4% in 2010, a relatively high value compared to most of the OECD countries. As a consequence, total green House Gas (GHG) emissions originated from the use fossil fuels in Israel are expected to rise sharply in 2030. The promotion of renewable energy, particularly solar is a way to deal with predicted rising emissions as well as addressing energy security and increase of oil price that a✏ict the Middle East region. Worldwide, solar cell electricity generation market has grown dramatically, both in terms of electricity generation and market size. A paradox that this study addresses is that while Israel has developed and exported advanced solar technology, it is among the last countries that actual use this type of technology for self consumption. For most of its history, Israel has been an energy-poor state, relying almost completely on imported fossil fuels to meet its energy needs. However, the Israeli energetic independence has been changed dramatically in 2009 when two large fields (nearly 3.1 Trillion Cubic Feet) of natural gas were discovered in the Mediterranean Sea 60 km o↵ the Israeli coast line. These discoveries have changed the energy market in Is-
Assessing Macrofinancial Implications and Resolution Policies of Nonperforming Loans

Empirical analysis of the determinants of NPLs examines the role of macroeconomic variables and of bank-specific factors in driving their movements. Evidence of the macroeconomic factors influencing credit risk points to the countercyclical behavior of NPLs (Klein 2013). An expansion in real gross domestic product (GDP) leads to an improvement in borrower repayment capacity, a reduction of default risk, and a decline in NPLs; economic contraction works in the opposite direction. More generally, better macroeconomic conditions—a decline in unemployment, inflation, currency depreciation, and global financial volatility, among other factors—constrain NPL ratios (Roy 2014; Ha, Trien, and Diep 2014; Lee and Rosenkranz 2019). In their examination of the bank-specific factors associated with higher NPLs in Asia, Lee and Rosenkranz (2019) point to decreased capitalization, lowered profitability, increased risk appetite, past loan growth, and fall in credit supply.
Analysis and Extraction of Electroencephalogram (EEG) wave for Brain-Computer Interfacing

: The present work demonstrates the mining of brain data using non-invasive methods by simply interfacing the brain and computing devices. This work attempts to analyze and collect the Electroencephalogram (EEG) signal by two different sensors for Brain-Computer-Interfacing (BCI) system. A detailed performance analysis is carried out between these two sensors. Then various signal processing techniques and algorithms are used to extract two useful features of the brain, attention and meditation. Finally, for the later portion of the paper, Brain’s attention (EEG Beta wave) and meditation (EEG Theta wave) values are conditioned successfully to make them available for a practical application.
1 Word order constraints on event-internal modifiers

Word order constraints on adverbials in German clauses have been subject to a long-standing debate. Regarding event-internal modifiers, such as comitatives and instrumentals, different, but class-based base positions have been proposed by Frey & Pittner (1998), and Maienborn (2001), among others. In this paper, we argue that serialization constraints on event-internal adverbials should not be formulated in terms of class-based (intrinsic) properties, but in terms of extrinsic properties, such as Anaphoricity, and Thematic Integration, which apply to the modifiers. In two experimental studies, we have been able to show that serializations of event-internal modifiers are more complex than envisaged in prior analyses, which do not take lexical variation into account. By relying on extrinsic properties to determine word order constraints, a more parsimonious analysis can be proposed. This analysis eliminates the need to postulate two different constraint systems for complements and adjuncts to determine word order regularities in the German Mittelfeld (at least for event-internal modifiers).
Derivation of Change Sequences from State-Based File Dierences for Delta-Based Model Consistency

In view-based software development, viewsmay share concepts and thus contain redundant or dependent information. Keeping the individual views synchronized is a crucial property to avoid inconsistencies in the system. In approaches based on a Single Underlying Model (SUM), inconsistencies are avoided by establishing the SUM as a single source of truth from which views are projected. To synchronize updates from views to the SUM, delta-based consistency preservation is commonly applied. This requires the views to provide negrained change sequences which are used to incrementally update the SUM. However, the functionality of providing these change sequences is rarely found in real world applications. Instead, only state-based dierences are persisted. Therefore, it is desirable to also support views which provide state-based dierences in delta-based consistency preservation. This can be achieved by estimating the ne-grained change sequences from the state-based dierences. This thesis evaluates the quality of estimated change sequences in the context of model consistency preservation. To derive such sequences, matching elements across the compared models need to be identied and their dierences need to be computed. We evaluate a sequence derivation strategy that matches elements based on their unique identier and one that establishes a similarity metric between elements based on the elements’ features. As an evaluation baseline, dierent test suites are created. Each test consists of an initial and changed version of both a UML class diagram and consistent Java source code. Using the dierent strategies, we derive and propagate change sequences based on the state-based dierence of the UML view and evaluate the outcome in both domains. The results show that the identity-based matching strategy is able to derive the correct change sequence in almost all (97 %) of the considered cases. For the similarity-based matching strategy we identify two reoccurring error patterns across dierent test suites. To address these patterns, we provide an extended similarity-based matching strategy that is able to reduce the occurrence frequency of the error patterns while introducing almost no performance overhead.