Miracle-dz/UniFAR-FTUs huggingface dataset:
Establishing Normative Values for Acromion Anatomy: A Comprehensive MRI-Based Study in a Healthy Population of 996 Participants

Shoulder pain is a common issue often linked to conditions such as subacromial impingement or rotator cuff lesions. The role of the acromion in these symptoms remains a subject of debate. This study aims to establish standardized values for commonly used acromion dimensions based on whole-body MRI scans of a large and healthy population and to investigate potential correlations between acromion shape and influencing factors such as sex, age, BMI, dominant hand, and shoulder pain. The study used whole-body MRI scans from the Study of Health in Pomerania, a German population-based study. Acromion index, acromion tilt, and acromion slope were measured. Interrater variability was tested with two independent, trained viewers on 100 MRI sequences before actual measurements started. Descriptive statistics and logistic regression were used to evaluate the results. We could define reference values based on a shoulder-healthy population for each acromion parameter within the 2.5 to 97.5 percentile. No significant differences were found in acromion slope, tilt, and index between male and female participants. No significant correlations were observed between acromion morphology and anthropometric parameters such as height, weight, or BMI. No significant differences were observed in acromion parameters between dominant and non-dominant hands or stated pain intensity. This study provides valuable reference values for acromion-related parameters, offering insight into the anatomy of a healthy shoulder. The findings indicate no significant differences in acromion morphology based on sex, weight, BMI, or dominant hand. Further research is necessary to ascertain the clinical implications of these reference values. The establishment of standardized reference values opens new possibilities for enhancing clinical decision making regarding surgical interventions, such as acromioplasty.
ACCOUNTABILITY ARISAN CULTURE BASED ON UKHUWAH ISLAMIYAH PERSPECTIVE

The purpose of this research is to analyze accountability arisan culture based on Ukhuwah Islamiyah perspective. The research was conducted in Bangkalan, Madura. The method used is interpretivist paradigm with qualitative approach. Qualitative data obtained by conducting interviews. The informants in this research are the Arab social gathering community and religious expert. Data analysis techniques in this study are data reduction, data presentation, validity, and drawing conclusions. The research found the meaning of receivable in arisan in broader context than existing concept of receivable in accounting, namely arisan as ukhuwah Islamiyah, arisan as trust relationship, arisan as social spiritual responsibility and has become a culture in the arisan. Sincerity to help fellow members is an accountability not only to society but also to God. The obligation to pay the arisan which is intended not only because of an obligation but is also interpreted as a form of accountability to humans (social) and God which is manifested in the form of ukhuwah Islamiyah.
Piezoelectric Ceramics and Flexible Printed Circuits’ Interconnection Using Sn58Bi Solder Anisotropic Conductive Films for Flexible Ultrasound Transducer Assembly

Interconnection technology using Sn58Bi solder anisotropic conductive films (ACFs) has been chosen to assemble piezoelectric ceramics on flexible printed circuits for ultrasound imaging applications. The bonding and dicing processes were performed, and the bending of test samples was evaluated. The results showed excellent integrity of solder ACFs’ interconnects compared with other Ni-/Au-coated polymer ball and Ni ball-based ACFs’ interconnects. The metallurgical interconnects of the solder ACFs produce lower electrical resistances after pressure cooker and bending reliability tests. Moreover, the solder ACFs with a high-speed bonding process resulted in more electrically conductive, more reliable, and finer-pitch bonding for producing higher process yield and higher density ultrasound transducer arrays.
Causal relationship of gut microbiota with diabetic nephropathy: a Mendelian randomization analysis

Background Patients with DN (diabetic nephropathy) show remarkable variations in their gut microbiota composition. However, to date, no study has shown whether a causal relationship exists between gut microbiota composition and DN. Methods Here, we performed a two-sample Mendelian randomization (MR) investigation for identifying causal associations of gut microbiota with DN. Gut microbiota genetic data were gathered from the recent genome-wide association study pooled data of the MiBioGen consortium, which included 24 cohorts and 18,340 individuals. Results IVW(Inverse variance weighting) revealed that Verrucomicrobia [odds ratio (OR) = 1.390; 95% confidence interval (CI) = 1.10–1.75; p = 0.005], Peptostreptococcaceae (OR = 1.284; 95% CI = 1.03–1.59; p = 0.012), Verrucomicrobiaceae (OR = 1.390; 95% CI = 1.10–1.75; p = 0.005), Akkermansia (OR = 1.390; 95% CI = 1.10–1.75; p = 0.005), Butyricimonas (OR = 1.261; 95% CI = 1.02–1.55; p = 0.031), Catenibacterium (OR = 1.278; 95% CI = 1.02–1.59; p = 0.030). Conclusion Two-sample MR analysis identified 12 microbial taxa in gut microbiota (one of which is yet to be officially named) that showed significant causal associations with DN; 8 of these taxa significantly increased the risk of DN, while the remaining 4 taxa (including the one without an official name) reduced the risk of DN. The precise mechanisms influencing the interactions of gut microbiota with DN occurrence remain unclear; hence, additional investigations should be conducted to clarify these mechanisms.
Spatial Patterns of Forest Ecosystem Services and Influencing Factors in the Ganjiang River Basin

Abstract: As the major component of terrestrial ecosystems, forests play an irreplaceable role in providing ecosystem services and products (e.g. biodiversity, carbon sequestration, water yield and timber). Spatially quantifying ecosystem services and interactions will shed light on sustainable forest management. Main forest ecosystem services including carbon storage, water yield, soil retention and wood volume in the Ganjiang River Basin (GRB) were evaluated and mapped through the integrated use of InVEST3.1. 0, CASA modeling and ArcGIS10.2, and relationships between forest ecosystem services and natural or social-economic factors were quantified and discussed based on ArcGIS10.2 and SPSS19.0. Results showed that the spatial pattern of the four ecosystem services is heterogeneous. Forests dominated by broad-leaved forest and bamboo forest in mountainous regions around the GRB provided the largest carbon storage and wood volume services, while forests dominated by Masson pine plantations or Chinese fir plantations in the northeast provided the largest water yield service. The spatial pattern of the soil retention service is more discrete than others, and forests in the southwestern regions showed larger soil erosion modulus than in the northeastern regions. Ecosystem services are closely related to the environmental process and human activities. With altitude or slope increases, the carbon storage and wood volume of forests increased and water yield depth and soil retention decreased. When the regional total population decreased or GDP per capita increased, carbon storage and wood volume increased. Further research into the interactions between environmental factors and ecosystem services is needed in order to understand environmental constraints when dealing with ecological problems.
Chemogenetic Activation of Excitatory Neurons Alters Hippocampal Neurotransmission in a Dose-Dependent Manner

Abstract Designer receptors exclusively activated by designer drugs (DREADD)-based chemogenetic tools are extensively used to manipulate neuronal activity in a cell type-specific manner. Whole-cell patch-clamp recordings indicate membrane depolarization, coupled with increased neuronal firing rate, following administration of the DREADD ligand, clozapine-N-oxide (CNO) to activate the Gq-coupled DREADD, hM3Dq. Although hM3Dq has been used to enhance neuronal firing in order to manipulate diverse behaviors, often within 30 min to 1 h after CNO administration, the physiological effects on excitatory neurotransmission remain poorly understood. We investigated the influence of CNO-mediated hM3Dq DREADD activation on distinct aspects of hippocampal excitatory neurotransmission at the Schaffer collateral-CA1 synapse in hippocampal slices derived from mice expressing hM3Dq in Ca2+/calmodulin-dependent protein kinase α (CamKIIα)-positive excitatory neurons. Our results indicate a clear dose-dependent effect on field EPSP (fEPSP) slope, with no change noted at the lower dose of CNO (1 μM) and a significant, long-term decline in fEPSP slope observed at higher doses (5–20 μM). Further, we noted a robust θ burst stimulus (TBS) induced long-term potentiation (LTP) in the presence of the lower CNO (1 μM) dose, which was significantly attenuated at the higher CNO (20 μM) dose. Whole-cell patch-clamp recording revealed both complex dose-dependent regulation of excitability, and spontaneous and evoked activity of CA1 pyramidal neurons in response to hM3Dq activation across CNO concentrations. Our data indicate that CNO-mediated activation of the hM3Dq DREADD results in dose-dependent regulation of excitatory hippocampal neurotransmission and highlight the importance of careful interpretation of behavioral experiments involving chemogenetic manipulation.
Development of oil extraction screening methodology taking into account innovative methods using the example of the Ukrainian field

The object of research in the paper is the process of fluid transfer through the pore space of the reservoir rock. The traditional method of estimating oil recovery by flooding has a large number of uncertainties. In this study, to address limitations of the current approach to determining oil production, let’s introduce a systematic algorithm aimed at enhancing result precision. The methodology for calculating the oil recovery coefficient for determining the amount of oil that can be extracted by flooding is presented. In this work, the step-by-step process of determining the oil recovery coefficient was analytically established, which achieves a certain degree of accuracy due to the inclusion of a number of methods of calculation of scientists from different countries of the world. In particular, the lithofacies distribution of the reservoir using the kriging method, the use of a representative elementary volume (REV) to increase the accuracy of determining the irreducible water saturation of each facies, and the use of the Buckley-Leverett equation in the calculation of the oil recovery coefficient are proposed. The number of facies (sandstone, argillaceous sandstone, siltstone) was determined on the example of the B-16n horizon of the «Ukrainian deposit» and the oil recovery coefficients were calculated for each separately (0.53, 0.47, 0.29). Further determination of the average oil recovery coefficient is described in the researched and requires close integration of the obtained data in three-dimensional space, as it allows to calculate the fraction of facies content in the reservoir volume. The use of the proposed action algorithm will help to build a more reliable three-dimensional hydrodynamic model, will lead to a much lower degree of uncertainty of reservoir properties, and in particular irreducible water saturation, as well as more accurate distribution of lithological properties using kriging. Also, this methodology for calculating the oil recovery coefficient involves the use of the Buckley-Leverett equation and fractional flow curves, the data of which are based on relative permeabilities and depend on the irreducible water saturation determined in the laboratory for each lithofacies. These techniques justify the collection of additional core material, the importance of lithofacies dismemberment of the formation and are closely integrated in the three-dimensional space, which makes it possible to simulate the existing processes, reproduce the proposed methodology and perform the forecast.
How to Measure Inequality of Opportunity: A Hands-On Guide

The measurement of inequality of opportunity is a growing topic in economics. In recent years many theoretical papers have been published and the number of empirical contributions to this literature has exploded in the last two decades. The increasing quality and availability of survey data will likely encourage further empirical research. Not surprisingly, journal articles and volume chapters have recently reviewed the main approaches to measuring inequality of opportunity and discussed the existing evidence. The aim of this paper is complementary to those contributions: it discusses the many practical issues that typically arise when measuring inequality of opportunity with survey data. The paper originates from my lecture notes for the workshop “Measuring inequality of opportunity” held at ISSR, The University of Queensland in February 2016. The workshop aimed at covering the main issues of the applied literature on inequality of opportunity measurement. The material is presented in an attempt to attract the interest of a multidisciplinary audience of social scientists and therefore does not get into the details of some more technical aspects.
Spatial prediction of flood-susceptible areas using frequency ratio and maximum entropy models

Abstract Modelling the flood in watersheds and reducing the damages caused by this natural disaster is one of the primary objectives of watershed management. This study aims to investigate the application of the frequency ratio and maximum entropy models for flood susceptibility mapping in the Madarsoo watershed, Golestan Province, Iran. Based on the maximum entropy and frequency ratio methods as well as analysis of the relationship between the flood events belonging to training group and the factors affecting on the risk of flooding, the weight of classes of each factor was determined in a GIS environment. Finally, prediction map of flooding potential was validated using receiver operating characteristic (ROC) curve method. ROC curve estimated the area under the curve for frequency ratio and the maximum entropy models as 74.3% and 92.6%, respectively, indicating that the maximum entropy model led to better results for evaluating flooding potential in the study area.
Correlations between Resting Electrocardiogram Findings and Disease Profiles: Insights from the Qatar Biobank Cohort

Background: Resting electrocardiogram (ECG) is a valuable non-invasive diagnostic tool used in clinical medicine to assess the electrical activity of the heart while the patient is resting. Abnormalities in ECG may be associated with clinical biomarkers and can predict early stages of diseases. In this study, we evaluated the association between ECG traits, clinical biomarkers, and diseases and developed risk scores to predict the risk of developing coronary artery disease (CAD) in the Qatar Biobank. Methods: This study used 12-lead ECG data from 13,827 participants. The ECG traits used for association analysis were RR, PR, QRS, QTc, PW, and JT. Association analysis using regression models was conducted between ECG variables and serum electrolytes, sugars, lipids, blood pressure (BP), blood and inflammatory biomarkers, and diseases (e.g., type 2 diabetes, CAD, and stroke). ECG-based and clinical risk scores were developed, and their performance was assessed to predict CAD. Classical regression and machine-learning models were used for risk score development. Results: Significant associations were observed with ECG traits. RR showed the largest number of associations: e.g., positive associations with bicarbonate, chloride, HDL-C, and monocytes, and negative associations with glucose, insulin, neutrophil, calcium, and risk of T2D. QRS was positively associated with phosphorus, bicarbonate, and risk of CAD. Elevated QTc was observed in CAD patients, whereas decreased QTc was correlated with decreased levels of calcium and potassium. Risk scores developed using regression models were outperformed by machine-learning models. The area under the receiver operating curve reached 0.84 using a machine-learning model that contains ECG traits, sugars, lipids, serum electrolytes, and cardiovascular disease risk factors. The odds ratio for the top decile of CAD risk score compared to the remaining deciles was 13.99. Conclusions: ECG abnormalities were associated with serum electrolytes, sugars, lipids, and blood and inflammatory biomarkers. These abnormalities were also observed in T2D and CAD patients. Risk scores showed great predictive performance in predicting CAD.
Guest Editorial, part of a Special Feature on Applied Research for Enhancing Human Well-Being and Environmental Stewardship: Using Complexity Thinking in Southern Africa Applied research for enhancing human well-being and environmental stewardship: using complexity thinking in Southern Africa

[Extract] Humans all over the planet are struggling and aspiring to engage with the scale and scope of the challenge of achieving human well-being and environmental stewardship for all. This special feature presents the products of processes in Southern Africa that have explored the potential use of complexity approaches to tackling the substantial social-ecological challenges in the region. Although the papers composing the special feature draw mainly on South African case studies, the thinking and participation in development processes were inclusive of the broader region. A concept that emerges through the papers is the inevitable conflation of human well-being and justice, and together they point toward social and ecological justice as an expression of human well-being, founded on environmental stewardship. Over the time the constituent papers have emerged, Mark Swilling and Eve Annecke have produced a most elegantly written and argued book Just Transitions (Swilling and Annecke 2012) that foregrounds the justice theme, deepens and complements several of the perspectives collectively presented in this feature, particularly complexity-based research, and adds an important economics lens.
Ulcerative colitis and pyoderma gangrenosum refractory to treatment successfully managed with pentoxifylline: a case report

Introduction and importance: Pyoderma gangrenosum is an unusual inflammatory pathology, with neutrophilic dermatosis, of unknown etiology. It is associated with diseases such as bowel disease. Generally, it is treated with anti-inflammatory drugs, corticosteroids, immunosuppressants, and antibodies against tumor necrosis factor, but relapse and adverse effects are persistent. Pentoxifylline is a drug with immunoregulatory and anti-inflammatory properties. Case presentation: A 47-year-old male with a diagnosis of ulcerative colitis initially managed favorably for 7 years with mesalazine. At 3 years of treatment, he presented a sudden ulcer that affected skin and subcutaneous tissue (13×10 cm) in the lower right limb. During the last 2 years, he was treated with mesalazine and infliximab with partial results and permanent relapses. Therefore, pentoxifylline was added to his treatment. Clinical discussion: The justification for the addition of pentoxifylline is mainly its action as an inhibitor of Nuclear Factor-kappa Beta (NF-κB) transcription, which stimulates the expression of proinflammatory interleukin genes such as IL-1, IL-6, IL- 8, and TNF-α and showing immunoregulatory and antioxidant activities. Conclusion: With pentoxifylline, this lesion healed at 6 weeks without relapses after 2 years.
Preliminary Screening of Brucella Antibodies in Sera of Persons in Contact with Animals in Mahlab 2-Hilat Koukou, Khartoum, Sudan in 2022

Brucellosis remains a major zoonosis worldwide. This study was intended to estimate Brucellosis prevalence among people living and working in a high stocking density area (Mahlab 2) and risk factors. A cross-sectional study was done among randomly selected males and females in the area of Mahlab 2. Data was collected using questionnaires and laboratory investigations. Blood samples were collected from participants. The Rose Bengal Plate (RBP) test was used for the detection of Brucella antibodies in serum samples and a modified Rose Bengal Plate (mRBP) test was used for confirmation. A total of 69 participants were enrolled in this study. The majority of those participants were between 18–29 years of age. The seropositivity of patients’ blood samples using these tests, was 28.4%. Socio-demographic characteristics, occupation, clinical signs of disease, types, and size of herds reared by animal owners, sanitary practices, and awareness about zoonosis, Brucellosis, and symptoms of Brucellosis showed no significant correlation with seropositivity among patients’ blood samples for Brucellosis. It is recommended that surveillance and extension programs should be carried out to evaluate the magnitude of Brucellosis and to increase awareness about it. For proper control and prevention to decrease the incidence in animals, hence decreasing the incidence in humans, animal vaccination is essential.
SeqNAS: Neural Architecture Search for Event Sequence Classification

Neural Architecture Search (NAS) methods are widely used in various industries to obtain high-quality, task-specific solutions with minimal human intervention. Event Sequences (EvS) find widespread use in various industrial applications, including churn prediction, customer segmentation, fraud detection, and fault diagnosis, among others. Such data consist of categorical and real-valued components with irregular timestamps. Despite the usefulness of NAS methods, previous approaches only have been applied to other domains: images, texts or time series. Our work addresses this limitation by introducing a novel NAS algorithm — SeqNAS, specifically designed for event sequence classification. We develop a simple yet expressive search space that leverages commonly used building blocks for event sequence classification, including multi-head self attention, convolutions, and recurrent cells. To perform the search, we adopt sequential Bayesian Optimization and utilize previously trained models as an ensemble of teachers to augment knowledge distillation. As a result of our work, we demonstrate that our method surpasses state-of-the-art NAS methods and popular architectures suitable for sequence classification and holds great potential for various industrial applications.