Miracle-dz/UniFAR-FTUs huggingface dataset:
Microstrip band-pass filter with −67 dB stop band up to 8.8 times the pass-band center frequency

Step-impedance resonators and step-impedance capacitor coupling pads are introduced to microstrip band-pass filters to suppress spurious stop-band responses up to the ninth order, thereby providing a very wide stop band. Combined with improvements in existing suppression techniques, the overall suppression in one of the filters, with 1 GHz center frequency and 42% bandwidth, is −54 dB, up to 8.9 GHz. By also using suitably placed resistors, spurious levels are now depressed to −67 dB up to 8.8 GHz, with only 0.03 dB extra pass-band loss.
Spatial filtering in a 6D hybrid-Vlasov scheme for alleviating AMR artifacts: a case study with Vlasiator, versions 5.0, 5.1, 5.2.1

Numerical simulation models that are used to investigate the near-Earth space plasma environment require sophis-ticated methods and algorithms together with high computational power. Vlasiator 5.0 is a hybrid-Vlasov plasma simulation code that is able to perform 6D (3D in ordinary space and 3D in velocity space) simulations using Adaptive Mesh Refinement (AMR). In this work we describe a side effect of using AMR in Vlasiator 5.0 where the heterologous grid approach creates discontinuities due to the different grid resolution levels. The discontinuities cause spurious oscillations in the electromagnetic 5 fields that alter the global results. We present and test a spatial filtering operator for alleviating this artifact without significantly increasing the computational overhead. We demonstrate the operator’s use case in large 6D AMR simulations and evaluate its performance with different implementations.
PIE-Net: Photometric Invariant Edge Guided Network for Intrinsic Image Decomposition - Supplementary

where, I is the final observed image. λ is the incoming wavelength of the light integrated over the entire visible spectrum ω. n⃗ denotes the surface normal while l⃗ denotes the incident light direction. m is a function denoting the interaction of n⃗ & l⃗. f indicates the spectral camera sensitivity. e describes the spectral power distribution of the illuminant. While ρ denotes the reflectance of the object. Discretising the model, we obtain:
Toward Human Cognition-inspired High-Level Decision Making For Hierarchical Reinforcement Learning Agents

Hierarchical reinforcement learning (HRL) methods aim to leverage the concept of temporal abstraction to eﬃciently solve long-horizon, sequential decision-making problems with sparse and delayed rewards. However, the decision-making process of the agent in most HRL methods is often based directly on low-level observations, while also using ﬁxed temporal abstraction. We propose the hierarchical world model (HWM), which can capture more ﬂexible high-level, temporally abstract dynamics, as well as low-level dynamics of the system. We posit such model is a natural extension to the HRL framework toward a decision-making process closer to that of humans.
Dissolved Constituents in Agricultural Drainage Waters

Efflux of dissolved solutes in agricultural subsurface drainage systems adversely affects the ecosystems of receiving waters, degrades soil fertility, and represents an economic loss to farmers. These solutes are frequently studied without regard to their associated ions, which play a fundamental role in their transport characteristics. In this study, we conducted a literature review to identify major dissolved constituents in agricultural drainage waters characteristic of central Iowa and pinpointed causes of variability in the leaching rate of these constituents. This literature review is complemented by a thorough field investigation that analyzes major solute concentrations with respect to seasonal conditions, common cropping systems, and relationships among ions. Results from this investigation reveal that primary dissolved constituents consist of bicarbonate, calcium, nitrate, magnesium, chloride, sodium, and sulfate (in order of decreasing ppm concentration). Analysis of seasonal drainage samples showed that bicarbonate, calcium, and magnesium were present at greater concentrations during the post-growing season, while nitrate and chloride concentrations were greatest during the growing season. Seasonal variability of sulfate and sodium was negligible. Continuous corn and corn in annual rotation with soybeans had greater magnesium and chloride concentrations than soybeans in annual rotation with corn. Conversely, calcium concentrations were greater for soybean cropping systems compared to corn cropping systems. Bicarbonate and nitrate were not significantly different among any of the cropping systems. A strong correlation between bicarbonate and calcium suggests that agricultural lime dissolution was caused by mineral weathering, rather than by acidification due to N fertilizer applications or nitrification. An analysis of observed drainage flows, pH, and temperatures suggested that these parameters were not good indicators of differences in ionic composition.
The state-of-art of Dynamic Global Illumination in video-games

Realistic Global Illumination is extremely costly. Video-games often preferred to pre-compute it, sacrificing dynamic lighting or moving geometry. However, more and more fully dynamic solutions are emerging. In this article, I will discuss the state-of-art of Dynamic Global Illumination methods that are used in video-games, giving you a brief explanation of how they work and listing their pros and cons.
Aerosol data assimilation with aqueous chemistry in WRF-Chem/WRFDA V4.3.1

This article introduces a new chemistry option in the Weather Research and Forecasting model data assimilation (WRFDA) system coupled with the WRF-Chem model (Version 4.3.1) to activate aqueous chemistry (AQCHEM) for the assimilation of surface concentrations of particulate matter (PM) along with atmospheric observations. The gas-phase mechanism used is the Regional Atmospheric Chemistry Mechanism (RACM), the inorganic aerosols are treated with the Modal Aerosol Dynamics Model for Europe (MADE), and secondary organic aerosol (SOA) production is parameterized based on the 5 Volatility Basis Set (VBS) approach. The "RACM-MADE-VBS-AQCHEM" scheme used in the weakly coupled data assimilation and forecast system facilitates aerosol-cloud-radiation-precipitation interactions through analysis and forecast cycling, accounting for both direct and indirect aerosol effects in the short-term air quality prediction. The new implementation in the three-dimensional variational data assimilation (3D-Var) system was tested with the assimilation of PM 2 . 5 and PM 10 concentrations on the ground over the East Asian region through month-long cycling for Spring 2019. It is demonstrated that the 10 inclusion of aerosol species in the aqueous (or cloud-borne) phase in both analysis and forecast reproduces aerosol wet removal processes in association with the development of clouds, systematically changing the atmospheric composition. The new option with aqueous chemistry in WRFDA is beneficial in air quality forecasting in cloudy conditions, while the simulations without aqueous chemistry overestimate surface PM 10 (PM 2 . 5 ) by a factor of 10 (3). All the simulations, data processing and analysis were conducted on NCAR’s supercomputer. 575 Author contributions. Ha developed the codes, designed the experiments, analyzed the results, and prepare the manuscript.
A Flexible Method of House Price Index Construction using Repeat-Sales Aggregates

The major issue which we address in this paper is the one-size-fits-all nature of the typical city-level house price index. In this vein, we make two contributions. First, we develop a new algorithm to ensure feasible estimation of geographically granular repeat-sales house price indices in cases of low transactions counts. This facilitates the estimation of a balanced panel of 63,122 Census tract-level repeat-sales house price indices (2010 definitions) at an annual frequency between 1989 and 2021, which we release alongside this paper. Second, we use these indices to estimate city-level house price indices that are robust to heterogeneous submarket appreciation and non-random sampling, two issues that confound classic approaches. Numerical simulations show this algorithm uncovers population indices even when house prices, quantities, and transaction sampling vary across locations and over time. This approach can be used in a flexible manner to calculate canonical price indices such as Lowe and Laspeyres, and more tailored summary indices on a variety of topics, including collateral valuation, climate risk assessment, or tracking changes to minority housing wealth over time.
ANTI DIABETIC POTENTIAL OF HERBAL PLANTS AND POLYHERBAL FORMULATION SOURCE LIKE PHYLLANTUS EMBLIKA AND ALOE BARBADENSIS

: Diabetes mellitus is caused by decreased insulin secretion. The people throughout the world increasingly affected by diabetes mellitus, a global problem. Due to side effects and other reasons usage of oral hypoglycemic agents is reduced. Globally, there will be an increase in the usage of herbal medicines for treating various diseases was reported. According to WHO all herbal medicines should be scientifically evaluated for their activities. In India from ancient time onwards herbal medicines were used to cure many diseases. Diabetes mellitus is cured by many medicinal plants. Many formulations were also formulated to treat diabetes mellitus but there is a lack of scientific validation so, the aim of this study is to select and scientifically validate a traditional polyherbal formulation. This review work is a small step towards scientifically studying the traditional polyherbal antidiabetic formulation, so as to standardize and improve the formulation for the benefit of humankind . traditional polyherbal formulation. This review work is a small step towards scientifically studying the traditional polyherbal antidiabetic formulation, so as to standardize and improve the formulation for the benefit of humankind . This It by or of which results or Effect Diabetic untreated rats showed significant (P<0.05) reduction in b.w. when compared to normal control rats. In glibenclamide-fed positive control rats, b.w. increased from 157.5 g to 167.08 g in 28 days of the experimental period. Similarly, on administration of active fractions, a gradual increase in b.w. was observed in diabetic-induced rats. Normal rats fed with active fraction showed b.w. almost similar to control rats. emblica antidiabetic as shown in its to reduce blood glucose level of STZ-indused diabetic This its in for the studies should be undertaken to identify the active antihyperglycemic compound comprehensive chemical pharmacological investigation should be carried out to isolet the and appropriate elucidation of its mechanism of action on of the aloe vera and phyllantus emblica in
Ego Strength and Self Actualization in relation to Burn out among Teachers working in Government Primary Schools, District Bilaspur, Himachal Pradesh.

: This study was conducted on 729 teachers working in Government Primary schools in District Bilaspur, Himachal Pradesh. The aim of study was to assess the effect of ego strength and self actualization on burn out. The standardized questionnaires were used to assess the ego strength, self actualization and burn out of the Teachers. The findings reveals that the mean/average scores of ego strength, self actualization and burn out of teachers were 19.72, 156.12 and 54.93(Emotional exhaustion = 26.61, Depersonalization= 13.28 and Personal accomplishment= 21.04) and there was no significant difference between male and female teachers as well as teachers belonging to rural and urban background on ego strength, self actualization and burn out( Emotional exhaustion, Depersonalization and Personal accomplishment). Results also reveals that there was a negative and significant relationship between ego strength and burn out (-.336 **) as well as its components (-.354 ** with emotional exhaustion, -.199 ** with depersonalization and -.299 ** with personal accomplishment) and results also further reveals that there was a negative and significant relationship between self actualization and burn out (-.145* ) as well as its components (-.135* with emotional exhaustion, -.111* with depersonalization and -.128* with personal accomplishment). The results of multiple regression analyses reveals that ego strength and self actualization were considered for the prediction of 13.6% emotional exhaustion, 4.9% depersonalization and 10% personal accomplishment and 12.6% overall burn out.
DUAL INPUT/OUTPUT DC-DC CONVERTER FOR SOLAR PV APPLICATIONS

: An inductor-based DC-DC converter with dual input and output (DIDO) is presented in this paper for renewable energy systems. SOC (State of Charge) control for battery and time-sharing control for switches has been proposed for power flow management between battery, solar PV, and standalone DC load. The converter integrates solar and battery sources at the input and provides a constant output for the load. The surplus energy is stored in the battery and can be utilized later in the absence of renewable energy sources. Both the input sources can power up the load individually and simultaneously. The converter operates in several modes depending upon the availability of input sources and load conditions. Sboost is main boost converter switch, and it will operate at both Dual Output Boost Mode (DOBM) and Dual Input Boost Mode (DIBM). The switches and diodes are used to set the battery as an output to store excess solar PV power and used to set battery as an input. The output capacitor and input capacitor are connected across the load and the input terminal respectively to reduce the output voltage and input voltage ripples. The steady state performance of the single stage converter has been explained with the relevant analytical expressions derived along with the characteristics. The simulation of the entire system is simulated by MATLAB- SIMULINK software and the characteristics are presented. A hardware prototype of the proposed system has been fabricated and dsPIC16F887 controller have been implemented. presented for dual input boost mode and dual output boost mode. Constant output voltage for various modes is obtained. The converter is capable of operating both in surplus and deficit PV power. Hardware results for various irradiations like partial shading, full shading is verified successfully.
HEART rate variability biofeedback for long COVID symptoms (HEARTLOC): protocol for a feasibility study

Introduction Long COVID (LC), also known as post-COVID-19 syndrome, refers to symptoms persisting 12 weeks after COVID-19 infection. It affects up to one in seven people contracting the illness and causes a wide range of symptoms, including fatigue, breathlessness, palpitations, dizziness, pain and brain fog. Many of these symptoms can be linked to dysautonomia or dysregulation of the autonomic nervous system after SARS-CoV2 infection. This study aims to test the feasibility and estimate the efficacy, of the heart rate variability biofeedback (HRV-B) technique via a standardised slow diaphragmatic breathing programme in individuals with LC. Methods and analysis 30 adult LC patients with symptoms of palpitations or dizziness and an abnormal NASA Lean Test will be selected from a specialist Long COVID rehabilitation service. They will undergo a 4-week HRV-B intervention using a Polar chest strap device linked to the Elite HRV phone application while undertaking the breathing exercise technique for two 10 min periods everyday for at least 5 days a week. Quantitative data will be gathered during the study period using: HRV data from the chest strap and wrist-worn Fitbit, the modified COVID-19 Yorkshire Rehabilitation Scale, Composite Autonomic Symptom Score, WHO Disability Assessment Schedule and EQ-5D-5L health-related quality of life measures. Qualitative feedback on user experience and feasibility of using the technology in a home setting will also be gathered. Standard statistical tests for correlation and significant difference will be used to analyse the quantitate data. Ethics and dissemination The study has received ethical approval from Health Research Authority (HRA) Leicester South Research Ethics Committee (21/EM/0271). Dissemination plans include academic and lay publications. Trial registration number NCT05228665.
Causal linkage of tobacco smoking with ageing traits: a Mendelian randomization analysis towards telomere attrition and frailty

BackgroundAgeing traits and frailty are important health issues in modern medicine. Evidence supporting the causal effects from tobacco smoking on various ageing traits is warranted. MethodsThis Mendelian randomization (MR) analysis instrumented 377 genetic variants associated with being an ever smoker in a genome-wide significant level to test the causal estimates from tobacco smoking. The outcome data included 337,318 white British ancestry UK Biobank participants. Leukocyte telomere length, appendicular lean mass index, subjective walking pace, handgrip strength, and wristband accelerometry determined physical activity degree were collected as ageing related outcomes. Summary-level MR by inverse variance weighted method and pleiotropy-robust MR methods, including weighted median and MR-Egger, was performed. ResultsSummary-level MR analysis indicated that higher genetic predisposition for tobacco smoking was significantly associated with shorter leukocyte telomere length [2-fold prevalence increase in smoking towards standardized Z-score, -0.041 (-0.054, -0.028)], lower appendicular lean mass index [-0.007 (-0.010, -0.005)], slower walking pace [ordinal category, -0.047 (-0.054, -0.033)], and lower time spent on moderate-to-vigorous physical activity [hours per week, -0.39 (-0.56, -0.23). The causal estimates were nonsignificant towards handgrip strength phenotype [kg, 0.074 (-0.055, 0.204)]. Pleiotropy-robust MR results generally supported the main causal estimates. ConclusionGenetically predicted tobacco smoking is significantly associated with worse ageing phenotypes. Healthcare providers may continue to reduce tobacco use which may be helpful to reduce the burden related to ageing and frailty.
Caregiving in a tertiary health institution in North Central Nigeria: Support types and financial burden

Background: Caregivers play an important role in informal patient management. Identification of the support types and the financial challenges faced by caregivers will provide information on strategies to ease this burden. This study aimed to describe the support types and financial burden amongst caregivers in a tertiary hospital in North Central Nigeria. Methods: This was a cross-sectional study conducted amongst caregivers of inpatients in a tertiary hospital in North Central Nigeria. Data were collected using a pre-tested interviewer-administered questionnaire and were analysed using the Statistical Package for the Social Sciences package version 23. Results were reported in frequencies and proportions and presented in prose, tables and charts. Results: A total of 400 caregivers were recruited. The mean age was 38.32 ± 12.82 years and most (66.0%) were females. Caregivers supported their patients by running errands (96.3%) and 85.3% reported caregiving as stressful. The reported errands were purchase of medications (92.3%), supply of non-medical needs (63.3%), submission of laboratory samples and collection of results (52.3%) and service payment (47.5%). About two-thirds (63.2%) reported loss of income while caregiving and about half (50.8%) provided financial support to the patients. Conclusion: This study suggests that majority of caregivers experience significant physical and financial burden while caregiving. This burden can be eased off by the simplification of payment and laboratory processes and employment of more staff to support patients admitted to the wards. The financial burden experienced by caregivers reinforces the need to encourage more Nigerians to enrol in a health insurance scheme.
Gait, physical activity and tibiofemoral cartilage damage: a longitudinal machine learning analysis in the Multicenter Osteoarthritis Study

Objective To (1) develop and evaluate a machine learning model incorporating gait and physical activity to predict medial tibiofemoral cartilage worsening over 2 years in individuals without advanced knee osteoarthritis and (2) identify influential predictors in the model and quantify their effect on cartilage worsening. Design An ensemble machine learning model was developed to predict worsened cartilage MRI Osteoarthritis Knee Score at follow-up from gait, physical activity, clinical and demographic data from the Multicenter Osteoarthritis Study. Model performance was evaluated in repeated cross-validations. The top 10 predictors of the outcome across 100 held-out test sets were identified by a variable importance measure. Their effect on the outcome was quantified by g-computation. Results Of 947 legs in the analysis, 14% experienced medial cartilage worsening at follow-up. The median (2.5–97.5th percentile) area under the receiver operating characteristic curve across the 100 held-out test sets was 0.73 (0.65–0.79). Baseline cartilage damage, higher Kellgren-Lawrence grade, greater pain during walking, higher lateral ground reaction force impulse, greater time spent lying and lower vertical ground reaction force unloading rate were associated with greater risk of cartilage worsening. Similar results were found for the subset of knees with baseline cartilage damage. Conclusions A machine learning approach incorporating gait, physical activity and clinical/demographic features showed good performance for predicting cartilage worsening over 2 years. While identifying potential intervention targets from the model is challenging, lateral ground reaction force impulse, time spent lying and vertical ground reaction force unloading rate should be investigated further as potential early intervention targets to reduce medial tibiofemoral cartilage worsening.
Identification and characterization of genetic risk shared across 24 chronic pain conditions in the UK Biobank.

Chronic pain is attributable to both local and systemic pathology. To investigate the latter, we focused on genetic risk shared among 24 chronic pain conditions in the UK Biobank. We conducted genome-wide association studies (GWAS) on all conditions and estimated genetic correlations among them, using these to model a factor structure in Genomic SEM. This revealed a general factor explaining most of the shared genetic variance in all conditions and an additional musculoskeletal pain-selective factor. Network analyses revealed a large cluster of highly genetically inter-connected conditions, with arthropathic, back, and neck pain showing the highest centrality. Functional annotation (FUMA) showed organogenesis, metabolism, transcription, and DNA repair as associated pathways, with enrichment for associated genes exclusively in brain tissues. Cross-reference with previous GWAS showed genetic overlap with cognition, mood, and brain structure. In sum, our results identify common genetic risks and suggest neurobiological and psychosocial mechanisms of vulnerability to chronic pain.
The global structure of iterated function systems

I study sets of attractors and non-attractors of finite iterated function systems. I provide examples of compact sets which are attractors of iterated function systems as well as compact sets which are not attractors of any iterated function system. I show that the set of all attractors is a dense Fs set and the space of all non-attractors is a dense Gd set it the space of all non-empty compact subsets of a space X. I also investigate the small trans-finite inductive dimension of the space of all attractors of iterated function systems generated by similarity maps on [0,1].