Evaluating the reasoning abilities of large language models (LLMs) solely from final answers can obscure failures in intermediate steps, especially in multi-hop QA benchmarks without step-level annotations. To address this gap, we introduce Omanic, an open-domain 4-hop QA benchmark designed not only to measure final-answer accuracy but also to diagnose where reasoning breaks down. Omanic contains 10,296 machine-generated training examples (OmanicSynth) and 967 expert-reviewed human-annotated evaluation examples (OmanicBench), with each evaluation question decomposed into single-hop sub-questions, intermediate answers, and structured graph topologies. Experiments with proprietary and open-source LLMs show that Omanic is challenging, while step-wise analysis reveals a later-hop bottleneck, factual knowledge floor, and error propagation along reasoning chains. Fine-tuning on OmanicSynth transfers to six reasoning and mathematics benchmarks, yielding a 7.41-point average gain and validating its effectiveness as supervision for reasoning-capability transfer. We release the data at https://huggingface.co/datasets/li-lab/Omanic and the code at https://github.com/XiaojieGu/Omanic.
In this work, we propose a preliminary design of a horizontal-axis wind turbine (HAWT) as a candidate for the Dhofar Wind Farm project, in the southern Omani Governorate "Dhofar", at the southwest part of the Sultanate of Oman. This wind farm (under construction) is considered to be the first commercial, utility-scale (50MW) wind farm in the GCC (Gulf Cooperation Council) area. The proposed wind turbine has an expected electricity generation of 2MW. We studied the wind atlas of Oman and from which we determined the maximum possible mean wind speed in the entire Sultanate and built our design based on that reference value, which is 6m/s (21.6km/h). After this, we applied a set of modeling equations that estimate the power output from the wind turbine rotor and matched the target electric power to the design variables using a MATLAB computer code. We reached a suitable design and we present here the distribution of the blade angle (twist angle), and the power per unit span along the rotor blade. The rotor design has 3 blades with a diameter of 70m and a rotational speed of 24rpm. This rotor gives 2.37MW of output power, which exceeds the target 2MW output, allowing for about 15% of p
Using observation records of wind speeds from weather stations in the Sultanate of Oman between 2000 and 2023, we compute estimators of the two Weibull distribution parameters (namely, the Weibull distribution's shape parameter and the Weibull distribution's scale parameter) in 10 weather station locations within eight Omani governorates. The 10 weather station locations in Oman and their corresponding governorates are Seeb (in Muscat), Salalah (in Dhofar), Buraimi (in Al Buraimi), Masirah (in Ash Sharqiyah South), Thumrait (in Dhofar), Sur (in Ash Sharqiyah South), Khasab (in Musandam), Sohar (in Sohar), Fahud (in Az Zahirah), and Saiq (in Ad Dakhiliyah). The obtained wind speed distributions at these weather stations are then used to predict the annual energy production (AEP) for a proposed reference amount of 1 MWp of wind turbine capacity, and this specific AEP is designated here by the term "normalized annual energy production (NAEP)." The direction of the wind is also analyzed statistically over the same period to identify the more probable wind directions. Four locations were clearly distinguishable as being windy compared to the others. The simulated probability of exceedin
As nations seek sustainable alternatives to fossil fuels, green hydrogen has emerged as a promising strategic pathway toward decarbonisation, particularly in solar-rich arid regions. However, identifying optimal locations for hydrogen production requires the integration of complex environmental, atmospheric, and infrastructural factors, often compounded by limited availability of direct hydrogen yield data. This study presents a novel Artificial Intelligence (AI) framework for computing green hydrogen yield and site suitability index using mean absolute SHAP (SHapley Additive exPlanations) values. This framework consists of a multi-stage pipeline of unsupervised multi-variable clustering, supervised machine learning classifier and SHAP algorithm. The pipeline trains on an integrated meteorological, topographic and temporal dataset and the results revealed distinct spatial patterns of suitability and relative influence of the variables. With model predictive accuracy of 98%, the result also showed that water proximity, elevation and seasonal variation are the most influential factors determining green hydrogen site suitability in Oman with mean absolute shap values of 2.470891, 2.37
Land cover and land use (LULC) changes are key applications of satellite imagery, and they have critical roles in resource management, urbanization, protection of soils and the environment, and enhancing sustainable development. The literature has heavily utilized multispectral spatiotemporal satellite data alongside advanced machine learning algorithms to monitor and predict LULC changes. This study analyzes and compares LULC changes across various governorates (provinces) of the Sultanate of Oman from 2016 to 2021 using annual time steps. For the chosen region, multispectral spatiotemporal data were acquired from the open-source Sentinel-2 satellite dataset. Supervised machine learning algorithms were used to train and classify different land covers, such as water bodies, crops, urban, etc. The constructed model was subsequently applied within the study region, allowing for an effective comparative evaluation of LULC changes within the given timeframe.
This paper discusses the issue regarding Non-verbal Autism Spectrum Disorder. It has been observed that this mental disorder is listed in major parts of the world including the US, UK, and India. To mitigate this type of disorder, a wide range of smartphones, computers, and artificial intelligence technologies have been used. This technology has helped the population cope with socialization and communication needs. Many applications have been developed to enhance the communication capabilities of non-verbal autistic children. This thesis project proposes the development of a platform that includes a web panel and an Android mobile application to assist non-verbal autistic children in communication, especially in Oman. Different interventions have been merged to improve the quality of life for people on the autism spectrum. The main problem identified in this case is that fragmented approaches are not suitable for autistic children. The augmented reality framework provides the capability to engage autistic children in creative play and self-reflection through interactive screen-based activities.
Since the start of its national renaissance in 1970, the Sultanate of Oman (Oman) has gone over a major development in several areas, such as education, infrastructure, and urbanization. This has been powered by the revenues from exporting crude oil and natural gas, which together form the skeleton of the country's economy. In the second half of 2014, the oil prices declined strongly to about 50% of its price. This was followed by another moderate decline in the second half of 2015 and the beginning of 2016, leaving the barrel price at a low level below 30 US$ in January 2016 (as compared to above 110 US$ in June 2014). This drop had direct impacts on the economy of Oman, manifested in a large budget deficit, reduced governmental expenditure, reduced or cancelled subsidy of fuels and electricity, increase in the water tariff, and decline in deposits in banks. The country is coping with this through its 9th five-year plan (2016-2020), which adopts a strategy of diversifying the income and relying less on the traditional oil and gas sector. The country has also taken measures to facilitate private businesses. This article sheds light on these topics as well as miscellaneous data abou
In this paper, we build a mathematical model for the dynamics of COVID-19 to assess the impact of placing healthy individuals in quarantine and isolating infected ones on the number of hospitalization and intensive care unit cases. The proposed model is fully analyzed in order to prove the positivity of solutions, to study the local and global stability of the disease-free equilibria and to drive the basic and control reproduction numbers of the model. Oman COVID-19 data is used to calibrate the model and estimate the parameters. In particular, the published data for the year 2020 is used, when two waves of the disease hit the country. Moreover, this period of time is chosen when no vaccine had been introduced, but only the non-pharmaceutical intervention (NPI) strategies were the only effective methods to control the spread and, consequently, control the hospitalization cases to avoid pressuring the health system. Based on the estimated parameters, the reproduction number and contribution of different transmission routes are approximated numerically. Sensitivity analysis is performed to identify the significant parameters in spreading the disease. Numerical simulation is carried o
In the scope of assessing aquifer systems in areas where freshwater is scarce, estimation of transit times is a vital step to quantify the effect of groundwater abstraction. Transit time distributions of different shapes, mean residence times, and contributions are used to represent the hydrogeological conditions in aquifer systems and are typically inferred from measured tracer concentrations by inverse modeling. In this study, a multi-tracer sampling campaign was conducted in the Salalah Plain in Southern Oman including CFCs, SF6, 39Ar, 14C, and 4He. Based on the data of three tracers, a two-component Dispersion Model (DMmix) and a nonparametric model with six age bins were assumed and evaluated using Bayesian statistics. In a Markov Chain Monte Carlo approach, the maximum likelihood parameter estimates and their uncertainties were determined. Model performance was assessed using Bayes factor and leave-one-out cross-validation. Both models suggest that the groundwater in the Salalah Plain is composed of a very young component below 30 yr and a very old component beyond 1,000 yr, with the nonparametric model performing slightly better than the DMmix model. All wells except one exh
The word E transformed everything is this world, as well as the whole globe itself. To a great extend this helps for eco friendly green world. In educational field, electronic medium has played a major role. It influenced and changed almost every component of it to electronic medium like e-book, online courses, etc. Throughout the world, leading universities are offering online courses voluntarily. Generally we refer to it as Massive Online Open Courses (MOOCs). There are many debates going on related to success and consequences of MOOCs. Many are highlighting that these courses are self-paced, economical, and provide quality training to all irrespective of geographical constraints. But many other academic people go against these points and keep listing many other disadvantages of MOOCs. This paper explores the basics of MOOCs at the initial section. Following section will deal with advantages and disadvantages of MOOCs in general. We the researchers collected the details about the awareness of MOOCs among teachers and students in a higher education institution in Oman. We have also collected the details about MOOCs implementation and usage within Oman educational society. Based on
The revolution of internet technology and its usage have led a significant increase in the number of online transactions and electronic data transfer, parallely increased the number of cybercrime incidents around the world. Steady economic growth in the Sultanate of Oman accelerated the volume of online utilization for e-commerce, banking, communication, education and so forth. Normally attackers target the users who ignore security practices due to the lack of information security awareness. Unawareness of information security practices, user negligence, lack of awareness programs and trainings are the root cause for information security threats. Earlier studies reveal there is a considerable and continuous cybercrime incident in Oman which compromises the security policy of the organizations, affecting the business continuity and the economic growth. In this study, a survey was performed among the educational institutions in Oman to investigate the level of information security awareness and based on the study, a security awareness model is proposed to enable information security practices in the educational institutions.
We performed a number of statistical analysis methods on the historical data for the air temperature at 2 m above the ground and its range, as reported by the database of NASA known as POWER, which stands for Prediction Of Worldwide Energy Resources. The point of analysis is the University of Buraimi, located in Al Buraimi Governate, in the Northwest of the Sultanate of Oman, near its border with United Arab Emirates (UAE). The data is in the form of a value per day, for every day in the year. The data analyzed span the period from January 3rd, 1981 (earliest day available) to December 31st, 2019 (latest end-of-year available). The statistical analysis methods include: simple linear regression, F-test: two-sample for variances, analysis of variance (ANOVA): single factor, and t-test: two-sample assuming equal variances (pooled). The results show that the mean of the local 2-meter air temperature is increasing at a rate of about 0.039 °C per year, starting from an estimated value of 27.4 °C in 1980. For the standard deviation of the 2-meter air temperature, and the mean and standard deviation of its range; although a linear regression analysis suggests a decline over time, the regre
Observational measurements hint at a peak in the quenching timescale of satellite galaxies in groups and clusters as a function of their stellar masses at $M_{\star} \approx 10^{9.5} \mathrm{M}_{\odot}$; less and more massive satellite galaxies quench faster. We investigate the origin of these trends using the EAGLE simulation in which they are qualitatively reproduced for satellites with $10^{9}<M_{\star}/\mathrm{M}_\odot<10^{11}$ around hosts of $10^{13}<M_\mathrm{200c}/\mathrm{M}_\odot<10^{14.6}$. We select gas particles of simulated galaxies at the time that they become satellites and track their evolution. Interpreting these data yields insights into the prevailing mechanism that leads to the depletion of the interstellar medium (ISM) and the cessation of star formation. We find that for satellites across our entire range in stellar mass the quenching timescale is to leading order set by the depletion of the ISM by star formation and stellar & AGN feedback in the absence of sustained accretion of fresh gas. The turnover in the quenching timescale as a function of stellar mass is a direct consequence of the maximum in the star formation efficiency (or equivalent
We present predictions for proper motions, infall times and times of first pericentric passage for 39 of M31's satellite galaxies. We estimate these by sampling satellite orbits from cosmological N-body simulations matched on mass, distance and velocity along the line of sight, in addition to properties of the host system. Our predictions are probabilistic based on repeated sampling from the uncertainty distributions of all quantities involved. We use these constraints on the satellites' orbital histories in conjunction with their published star formation histories to investigate the dominant environmental mechanisms for quenching satellites of M31-like hosts. Around half of the satellites appear to have quenched before their first pericentric passage around M31. Only the most massive satellites (with stellar masses > 10^8 M_sun) are able to maintain star formation for up to billions of years after infall. The majority of faint satellites, with stellar masses < 10^8 M_sun , were likely quenched before entering the M31 system. We compare our results for M31 against predictions for the Milky Way's satellites from the literature; M31's has a more active recent accretion history
We present a study of the neutral atomic hydrogen (HI) content of spatially resolved, low-redshift galaxies in the SIMBA cosmological simulations. We create synthetic HI data cubes designed to match observations from the Apertif Medium-Deep HI imaging survey, and follow an observational approach to derive the HI size-mass relation. The HI size-mass relation for SIMBA is in broad agreement with the observed relation to within 0.1 dex, but SIMBA galaxies are slightly smaller than expected at fixed HI mass. We quantify the HI spectral ($A_{\mathrm{flux}}$) and morphological ($A_{\mathrm{mod}}$) asymmetries of the galaxies and motivate standardizing the relative spatial resolution when comparing values in a sample that spans several orders of magnitude in HI mass. Galaxies are classified into three categories (isolated, interacted, or merged) based on their dynamical histories over the preceding ~2 Gyr to contextualize disturbances in their HI reservoirs. We determine that the interacted and merged categories have higher mean asymmetries than the isolated category, with a larger separation between the categories' $A_{\mathrm{mod}}$ distributions than between their $A_{\mathrm{flux}}$ d
We quantify departures from hydrodynamical and centrifugal equilibrium in the gas discs of low-mass ($10^{10.75}<M_\mathrm{200c}/\mathrm{M}_\odot<10^{11}$) galaxies from the COLIBRE cosmological hydrodynamical simulations. We evaluate the full Eulerian acceleration balance in the midplane and show that disequilibrium is widespread: equilibrium-based circular velocity estimates typically have errors of $\geq 10$ per cent ($\approx 75$ per cent of midplane gas by mass). Disequilibrium is strongest and the largest associated errors occur in the inner few kiloparsecs that are crucial for constraining the dark matter density profile. Correcting the circular velocity to account for pressure and convective terms does not reliably improve its recovery in strongly perturbed systems where time-dependent forces dominate the residual acceleration budget. Stellar feedback, self-gravitating gas clumps and AGN energy injection account for most strong local perturbations, and large-scale gravitational asymmetries act as a scaffold for disequilibrium. We classify gas discs into coherent, perturbed, and slow/erratic rotators and show that this classification correlates with galaxy properties l
We present the HI distribution, kinematics, mass modeling, and disk stability of the dwarf irregular galaxies ESO444-G084 and [KKS2000]23 using high-resolution, high-sensitivity MHONGOOSE survey data from MeerKAT. ESO444-G084 shows centrally concentrated HI emission, while [KKS2000]23 exhibits irregular high-density clumps. Total HI fluxes measured down to 10^19 and 10^18 cm^-2 are nearly identical, indicating that the increased HI diameter at lower column densities results mainly from the larger beam, with no significant extra emission detected. We derive total HI masses of (1.1 +/- 0.1) x 10^8 and (6.1 +/- 0.3) x 10^8 solar masses for ESO444-G084 and [KKS2000]23, respectively. Using PyFAT and TiRiFiC, we extract 3D rotation curves that reveal disk-like kinematics in both galaxies. ESO444-G084 shows a warp beyond ~1.8 kpc and a fast-rising curve consistent with a centrally concentrated dark matter distribution, while [KKS2000]23's more gradual rise suggests a more extended halo. Mass modeling with an isothermal halo and stellar mass-to-light ratios of 0.20 for ESO444-G084 and 0.18 for [KKS2000]23 yields consistent results. We analyze disk stability using spatially resolved Toomre
An avenue for understanding cosmological galaxy formation is to compare morphometric parameters in observations and simulations of galaxy assembly. In this second paper of the ASymba: Asymmetries of HI in SIMBA Galaxies series, we measure atomic gas HI asymmetries in spatially-resolved detections from the untargetted WALLABY survey, and compare them to realizations of WALLABY-like mock samples from the SIMBA cosmological simulations. We develop a Scanline Tracing method to create mock galaxy HI datacubes which minimizes shot noise along the spectral dimension compared to particle-based methods, and therefore spurious asymmetry contributions. We compute 1D and 3D asymmetries for spatially-resolved WALLABY Pilot Survey detections, and find that the highest 3D asymmetries A3D>0.5 stem from interacting systems or detections with strong bridges or tails. We then construct a series of WALLABY-like mock realizations drawn from the SIMBA 50 Mpc simulation volume, and compare their asymmetry distributions. We find that the incidence of high A3D detections is higher in WALLABY than in the SIMBA mocks, but that difference is not statistically significant (p-value = 0.05). The statistical p
SWIFTGalaxy is an open-source astrophysics module that extends SWIFTSimIO to analyses of particles belonging to individual galaxies simulated with SWIFT. It inherits from and extends the functionality of SWIFTSimIO's SWIFTDataset class. It understands the content of halo catalogues and therefore which particles belong to a galaxy or other group of particles, and its integrated properties. The particles occupy a coordinate frame that is enforced to be consistent, such that particles loaded on-the-fly will match e.g.~rotations and translations of particles already in memory. Intuitive masking of particle datasets is also enabled. Utilities to make working in cylindrical and spherical coordinate systems more convenient are also provided. Finally, tools to iterate efficiently over multiple galaxies are provided.
We present a novel method of combining kinematic models obtained at multiple spatial resolution levels in a self-consistent manner. The MHONGOOSE survey has mapped atomic hydrogen emission in $30$ nearby dwarf and spiral galaxies. Each galaxy is imaged at multiple resolution levels with unprecedented dynamic range in spatial resolution (from $\sim 10''$ to $ 90''$) and HI sensitivity, with the latter varying by almost a factor of $30$ across all resolution scales. We use radial weighting functions to combine kinematic models from all resolution levels. The weights are derived from the residuals of model fits to a set of observations of synthetic model galaxies with known rotation curves and geometries. We obtain combined (weighted and smoothed) inclination and position angle profiles for each galaxy. These suppress the sharp, often unphysical radial fluctuations arising in single-resolution profiles. We then fit the rotation speed and velocity dispersion profiles at each resolution level with the geometric profiles fixed to the combined profiles, finally combining these using the same weighting and smoothing approach. The combined rotation curves utilise all of the available inform