bluuebunny/crossref_metadata_2025_split huggingface dataset:
Risk Management for Cash Waqf Institutions Based on Good Corporate Governance Perspective: Lessons Learned from an Islamic Rural Bank in Indonesia
Authors: Rahmah Mawadah Atina , Abdurrubi Perwiragama Salman , Mujib Abdul 
Published: June 2023

Waqf, including cash waqf, is one of the Islamic social finance instruments that has been playing a significant role to develop community welfare throughout the history of Islam. Nowadays, Cash waqf significantly grows globally in countries like Saudi Arabia, Egypt, Kuwait, Turkey, Bangladesh, Malaysia, and Singapore. The unique feature of cash waqf is though it is subject to value volatility, shariah imposes that the value of cash waqf should not depreciate hence appreciation is required. Involving different parties in the process of cash waqf management, several risks may arise including moral hazards, conflict of interest, non-shariah compliance events, and so on. Thus, risk management becomes a must in managing cash waqf. Studies have deliberated on this issue and concluded with various findings. This study aims to use a Good Corporate Governance (GCG) perspective to examine risk management in the management of cash waqf at BPRS Barokah Dana Sejahtera. A qualitative method using semi-structured interviews was deployed to obtain primary data which has some extent of more comprehensive information to be analyzed rather than secondary data. This study concludes with some points including advantageous impacts on Cash Waqf Management Institution (LKS-PWU) regarding financial performance and the mauquf alaih nuance resulting from effective risk management. Moreover, the implementation of GCG principles as a framework for risk management in Cash Waqf institutions encourages the community to continuously contribute to cash waqf through LKS-PWU.
Loss of the Secretin Receptor Impairs Renal Bicarbonate Excretion and Aggravates Metabolic Alkalosis in Mice during Acute Base-Loading
Authors: Berg Peder , Jensen Tobias , Andersen Jesper Frank , Svendsen Samuel L , Modvig Ida Maria , Wang Tobias , Frische Sebastian , Chow Billy K. C. , Malte Hans , Holst Jens Juul , Sørensen Mads Vaarby , Leipziger Jens 
Published: June 2023

Significance Statement
During acute base excess, the renal collecting duct β-intercalated cells (β-ICs) become activated to increase urine base excretion. This process is dependent on pendrin and cystic fibrosis transmembrane regulator (CFTR) expressed in the apical membrane of β-ICs. The signal that leads to activation of this process was unknown. Plasma secretin levels increase during acute alkalosis, and the secretin receptor (SCTR) is functionally expressed in β-ICs. We find that mice with global knockout for the SCTR lose their ability to acutely increase renal base excretion. This forces the mice to lower their ventilation to cope with this challenge. Our findings suggest that secretin is a systemic bicarbonate-regulating hormone, likely being released from the small intestine during alkalosis.

Background
The secretin receptor (SCTR) is functionally expressed in the basolateral membrane of the β-intercalated cells of the kidney cortical collecting duct and stimulates urine alkalization by activating the β-intercalated cells. Interestingly, the plasma secretin level increases during acute metabolic alkalosis, but its role in systemic acid–base homeostasis was unclear. We hypothesized that the SCTR system is essential for renal base excretion during acute metabolic alkalosis.

Methods
We conducted bladder catheterization experiments, metabolic cage studies, blood gas analysis, barometric respirometry, perfusion of isolated cortical collecting ducts, immunoblotting, and immunohistochemistry in SCTR wild-type and knockout (KO) mice. We also perfused isolated rat small intestines to study secretin release.

Results
In wild-type mice, secretin acutely increased urine pH and pendrin function in isolated perfused cortical collecting ducts. These effects were absent in KO mice, which also did not sufficiently increase renal base excretion during acute base loading. In line with these findings, KO mice developed prolonged metabolic alkalosis when exposed to acute oral or intraperitoneal base loading. Furthermore, KO mice exhibited transient but marked hypoventilation after acute base loading. In rats, increased blood alkalinity of the perfused upper small intestine increased venous secretin release.

Conclusions
Our results suggest that loss of SCTR impairs the appropriate increase of renal base excretion during acute base loading and that SCTR is necessary for acute correction of metabolic alkalosis. In addition, our findings suggest that blood alkalinity increases secretin release from the small intestine and that secretin action is critical for bicarbonate homeostasis.
Earthquake-Triggered Crustal Shear Velocity Change at the Erupting Turrialba Volcano
Authors: Lynner Colton , Beck Susan L. 
Published: June 2023

ABSTRACT
Monitoring variations in seismic velocities surrounding active volcanoes provides insights into crustal deformation caused by eruptions and earthquakes. Turrialba volcano in Costa Rica has been erupting sporadically since 2010 and experienced a local seismic swarm in 2016, including the Mw 5.5 Capellades earthquake. It is thus an ideal natural laboratory to study crustal velocity changes associated with a seismic event at an active volcano. We use seismic noise-generated surface waves to characterize emergent upper crustal velocity variations following the earthquake sequence off the flank of the volcano. Our study highlights a rapid velocity drop immediately following the earthquake implying widespread damage and/or a readjustment of local stress. From the frequency dependence of surface waves, we find that the depth over which the velocities vary is localized to the upper ∼2.5 km of the crust, coinciding with the depth extent of the Capellades earthquake aftershock sequence as well as the shallow magma chamber feeding the Turrialban eruption. From the areal extent of the velocity decrease, crustal variations are likely tied to both damage following the seismic sequence and the evolution of the shallow magma reservoir feeding Turrialba.
Obraz ekologii we współczesnym świecie
Authors: Lubiarz Magdalena 
Published: June 2023

Artykuł prezentuje różnorodność zagadnień, do których bezpośrednio lub pośrednio odnosi się ekologia jako dyscyplina nauk biologicznych. Ekologia jest łączona ze zrównoważonym rozwojem, ochroną bioróżnorodności, usługami ekosystemowymi, przeciwdziałaniem zanieczyszczeniom środowiska, czy nowoczesnymi technologiami prośrodowiskowymi. Wielorakie postrzeganie ekologii wynika po części z interdyscyplinarności zagadnień podejmowanych w zakresie ekologii, ale także z nadużywania terminów „ekologia” i „ekologiczny” w mediach, biznesie, reklamie czy języku potocznym. Celem artykułu nie jest jednak wskazywanie jak ekologia powinna być postrzegana. Warto jednak podkreślić, że istotą badań ekologicznych jest zrozumienie interakcji zachodzących w środowisku naturalnym, aby możliwe było opracowanie skutecznych narzędzi jego ochrony.
La solución nutritiva, vermicomposta y micorrizas sobre el rendimiento y calidad de Lilium hybrida ´Indian Summerset´
Authors: Cárdenas-Hidalgo D , Urbina Sánchez Elizabeth , Valdez-Aguilar LA , Alejo-Santiago G , Vásquez-García LM , Reyes-Alemán JC 
Published: June 2023

Lilium es de los cultivos más importantes en el Estado de México, sus altos volúmenes de producción, asociados al uso de grandes cantidades de fertilizantes químicos, incrementan salinidad y alteran las propiedades físico-químicas y biológicas del suelo. El objetivo fue evaluar el efecto de las concentraciones de amonio en la solución nutritiva, el suministro de vermicomposta y micorrizas, así como sus interacciones sobre el crecimiento y calidad de Lilium hybrida var. ‘Indian Summerset’. Se plantaron bulbos en cajas con suelo franco arenoso, con o sin vermicomposta y con o sin micorrizas. Los riegos se realizaron con la solución de Steiner a 0.24 atm con tres relaciones de nitrato:amonio 100:0 %, 92.5:7.5 % y 87.5:12.5 %, y se compararon con fertilización convencional. Se conformó un diseño completamente al azar con arreglo factorial 4x2x2, los factores fueron amonio, vermicomposta y micorrizas. La solución nutritiva con 12.5 % de amonio incrementó altura de planta, peso seco, la concentración de K en hoja, y adelantó la floración y punto de corte. El aporte de vermicomposta y micorrizas no afectaron las variables de calidad. La vermicomposta al 5 % incremento la concentración de nitrógeno y potasio en hojas.
Editorial El ENIIU: un espacio para el fomento de las vocaciones científicas
Authors: Vargas Hernández Diana Vargas Hernández 
Published: June 2023

Nuevamente la Revista Habitus presenta una selección especial de trabajos presentados en el Encuentro de Investigación Universitaria (ENIIU), que llega a su sexta versión. Este evento científico es organizado anualmente por las universidades pertenecientes al Consejo Departamental de Educación Superior de Boyacá (CODES)[2], que incluye a las instituciones públicas y privadas con más presencia y tradición en el departamento.
El ENIIU supone un esfuerzo interinstitucional con un propósito claro: hacer visible el trabajo investigativo realizado por los estudiantes ―nacionales e internacionales―, tanto en semilleros de investigación como en fase de trabajos de grado de pregrado o posgrado. El ENIIU está diseñado para destacar el papel de los estudiantes como investigadores en formación y dar a conocer el alcance de sus trabajos desde una perspectiva interdisciplinar.
En este escenario convergen la juventud, la curiosidad y la rigurosidad, orientadas a pensar y a comunicar las posibles soluciones científicas a diferentes situaciones problémicas del entorno. También es una apuesta didáctica para resaltar el papel de los estudiantes y la importancia de consolidar sus vocaciones científicas.

[1]
[2] La Universidad Pedagógica y Tecnológica de Colombia (UPTC), la Universidad Santo Tomás (Seccional Tunja), la Universidad Nacional Abierta y a Distancia (UNAD), la Universidad Antonio Nariño (UAN), la Universidad de Boyacá, la Fundación Universitaria Juan de Castellanos y la Escuela Superior de Administración Pública
The effect of learner-generated digital materials on learners’ deep learning approach and self-efficacy
Authors: Alwafi Enas Mohammad 
Published: June 2023

This study aimed to explore the effect of learner-generated digital materials on students’ deep learning approach and self-efficacy. A quasi-experimental design that involves a pre-test, a post-test, a control group and an experiment group was used in this study which involved 51 students (25 students participated in the control group and 26 students participated in the experiment group). A questionnaire was used to measure students’ deep learning approach and self-efficacy. The study found that students in the experimental group improved their deep learning approach and self-efficacy more than students in the control group. Learner-generated digital materials can enhance students’ learning experiences. This study contributes new knowledge about the methods by which learner-generated digital material can be used as a learning approach. It also provides insight on how digital tools can be used to support students learning. This study provides recommendations for employing learner-generated digital materials to engage students in the learning experience.
Les crises forestières dans le Grand Est : un défi pour la filière bois aujourd’hui. Menaces ou opportunités pour demain ?
Authors: Renaud Jean-Pierre , Lévy Frédéric , Sauvestre Gilles 
Published: June 2023

Les forêts dans la région Grand Est représentent un enjeu économique et territorial considérable. Les dépérissements subis par ces forêts depuis 2018 ont décimé des milliers d’hectares et concernent la plupart des essences présentes, à commencer par l’Épicéa en plaine, très touché par les attaques de scolytes. Les conséquences pour la filière bois sont considérables, avec la récolte anticipée de millions de m3, l’engorgement des marchés et les difficultés pour valoriser un bois de qualité dépréciée. Des solutions d’urgence ont pu être trouvées pour faire face à la crise. Des pistes d’actions sont avancées pour prévenir d’autres crises, dont l’occurrence est prévisible avec les conséquences des changements climatiques.
Messages clésLa crise « scolytes » récente est liée à des conditions météorologiques exceptionnelles.Elle a provoqué des dépérissements inédits d’épicéas.Les conséquentes sur la filière bois sont très importantes.
A hybrid system for multi-step mortality rate forecasting
Authors: Duarte Filipe Coelho de Lima , Neto Paulo S. G. de Mattos , Firmino Paulo Renato Alves 
Published: June 2023

Abstract
Forecasting mortality is challenging. In general, mortality rate forecasting exercises have been based on the supposition that predictors residuals are random noise. However, issues regarding model selection, misspecification, or the dynamic behavior of the temporal phenomenon lead to biased or underperformed single models. Residual series might present temporal patterns that can still be used to improve the forecasting system. This paper proposes a new multi-step Hybrid System for Mortality Forecasting (HyS-MF) that combines ARIMA with N-BEATS. HyS-MF employs (i) ARIMA to model the mortality time series and (ii) one expert N-BEATS to forecast the residuals in each specific time horizon. The final output is generated by summing ARIMA with the N-BEATS forecasts in each time horizon. HyS-MF achieved a Mean Absolute Percentage Error (MAPE) average less than 1.6% considering all prediction horizons, beating statistical techniques, machine learning models, and hybrid systems considering 20 different time series from the French population mortality rate.
Interpretable Deep Learning Model for Crop Yield Prediction: A Case Study of Wheat Yield Prediction in Egypt.
Authors: Osibo Benjamin Kwapong , Ma Tinghuai , Wahab Mohamed Magdy Abdel , Jia Li , Wenzheng Ye , Bediako-Kyeremeh Bright , Osei-Appiah Stephen 
Published: June 2023

Abstract
Accurately predicting crop yield can be challenging due to the environmental, biological and technological factors that directly influence crops and farms. However, proper estimation of crop yield is of great importance to food security and crop harvest management. Recent studies have shown that machine learning (ML) or deep learning (DL) techniques can be used effectively for crop yield prediction due to their ability to capture patterns and make accurate predictions in time series data. In this study, we present an attention-based long short-term memory (LSTM) and extreme gradient boosting (XGB) hybrid regressor model for crop yield prediction. The LSTM block is trained to capture the temporal dependencies and also learn features from the time series input data, while the XGB is used to make predictions based on the trained extracted LSTM features. The dataset used in this research comprises average yield, climatic variables, soil and moderate-resolution imaging spectroradiometer (MODIS) data. Also, to deal with the black box nature associated with ML and DL models, we employ the explainable artificial intelligence (XAI) tool SHAP to interpret how our proposed LSTM-XGB method made predictions. Furthermore, we compared the performance of our proposed method to three other state-of-the-art (SOTA) models; LSTM, light gradient boosting machine regressor (LGBMR) and deep neural network (DNN). Results from our experiment show the superior performance of our proposed hybrid LSTM-XGB in comparison to other methods.
Humoral immune response to omicron infection in long-term Wuhan-Hu-1-imprinted population
Authors: Lu Yingying , Zhu Yufang , Zheng Yulan , Tang Lu , Chen Hui , Zhou Caili , Luo Jiayuan , Yang Xuejiao , Yu Lu , Hu Qiyan , Zhang Ruihua , Cui Miao , Lu Aili , Liu Feng , Xu Yunsheng , Zheng Zhihua , Cheng Zhengjiang , Hong Peng 
Published: June 2023

Abstract
Recent WHO vaccination guidance no longer recommends COVID-19 vaccination beyond the first booster in low risk population, citing high population-level hybrid immunity due to widespread omicron infections.1 Although SARS-CoV-2 infection confers durable protection against reinfection,2-4 it may also produce immune imprinting, which skews subsequent immune response to variant antigens toward the first-exposed antigen based on the antigenic distance.5,6 China has the earliest and exclusively Wuhan-Hu-1(WH1)-imprinted population before the 2022 nation-wide omicron outbreak,7 which offers a unique opportunity to study long-term immune imprinting between most antigenically distant strains. Here, we assessed pseudovirus neutralization activity and anti-WH1 receptor binding domain (RBD) antibodies in 4 Chinese cohorts with hybrid or vaccine-only imprinting, or naïve to SARS-CoV-2 prior to omicron BF.7 infection. Both hybrid and vaccine-only imprinting augmented post-infection serum neutralization of WH1 and omicron sub-variants BF.7/BQ.1.1/XBB.1.5 comparing to naïve background. Feedback from pre-existing high-affinity antibodies limited the magnitude of humoral immune response to omicron infection without compromising protection, while antigenic seniority of pre-existing cross-reactive B cells only slightly reduces forward neutralization breadth in hybrid- and RBD vaccine-imprinted participants. Our results support the effectiveness of hybrid immunity against omicron reinfection in long-term imprinted population and provide immunological basis for similar epidemiological findings.8-10
Clinical study of drug-loaded calcium sulfate in the treatment of hematogenous osteomyelitis in children
Authors: Liu Dun , Rehemutula Aierken , Si Yu , Zhou Hong yu , Li Jing yang , Chen Zi hao , Li Li 
Published: June 2023

Abstract
Background
At present, good results have been obtained in the treatment of hematogenous osteomyelitis(HO) in children by the use of drug-loaded calcium sulfate, but there are few clinical studies reported. The aim of this study was to investigate the clinical efficacy of radical debridement combined with drug-laden calcium sulphate antibiotics in paediatric haematogenous osteomyelitis.
Methods
In this study, we retrospectively analyzed the clinical data of 15 cases of pediatric hematogenous osteomyelitis admitted to our hospital in recent years. A total of 15 pediatric patients with HO treated in our hospital from January 2018 to February 2022 were included for evaluation.
Results
All 15 patients were treated with drug-laden calcium sulfate, and the antibiotic of choice was vancomycin in 14 cases and vancomycin combined with gentamicin in 1 case. The follow-up period ranged from 12 to 36 months, with a mean follow-up time of 24.73 months, and all children were treated with drug-laden calcium sulfate with satisfactory clinical outcomes. The results of serological examination showed that the preoperative white blood cell count level, C-reactive protein and erythrocyte sedimentation rate were higher than the postoperative ones, and the differences were statistically significant (P < 0.05).After the operation, referring to the treatment standard of McKee's osteomyelitis, 15 cases were cured without recurrence; According to the Lower Extremities Functional Scale, 12 cases were excellent, 2 cases were good and 1 case was moderate, with an excellent rate of 93.33%. Children with lower limb involvement could walk with full weight bearing, and gait was basically normal.
Conclusion
Drug-loaded calcium sulfate is a good therapeutic
Ultraflexible, cost-effective and scalable polymer-based phase change composites for wearable thermal management
Authors: Jing Yaoge , Zhao Zhengchuang , Cao Xiaoling , Sun Qinrong , Li Tingxian , Yuan Yanping 
Published: June 2023

Abstract
Phase change materials (PCMs) offer great potential for realizing zero-energy thermal management due to superior thermal storage and stable phase-change temperature. However, the liquid leakage and solid rigidity of PCMs are two long-standing challenges for PCM-based wearable thermal management applications. Herein, a facile and cost-effective strategy is reported, which utilizes the peroxide radical-initiated mechanism to develop ultraflexible polymer-based phase change composites with a dual 3D crosslinked network of olefin block copolymers (OBC) and styrene-ethylene-butylene-styrene (SEBS) inside PCMs. The synergistic effect of OBC-SEBS dual network on brittleness and elasticity enhancement enables the resultant paraffin wax (PW) composites of PW@OBC-SEBS to present outstanding flexibility (strain at break of 20-560%), high latent heat enthalpy (~ 176 J/g), superior thermal stability, and leakage-proof properties. Notably, the proposed peroxide-assisted sequential blending approach overcomes the limitations of traditional heavy processing equipment, achieving low-cost and efficient large-scale production. Furthermore, the applicability of a portable and flexible PW@OBC-SEBS module for wearable thermal management is demonstrated. The energy module can maintain a thermal comfort temperature range of 39-41°C, highlighting the realization of stable temperature control for personal thermotherapy. Our work provides a promising route to fabricate scalable and flexible polymer-based phase change composite for wearable thermal management.
COMBSS: Best Subset Selection via Continuous Optimization
Authors: Moka Sarat , Liquet Benoit , Zhu Houying , Muller Samuel 
Published: June 2023

Abstract
The problem of best subset selection in linear regression is considered with the aim to find a fixed size subset of features that best fits the response. This is particularly challenging when the total available number of features is very large compared to the number of data samples. Existing optimal methods for solving this problem tend to be slow while fast methods tend to have low accuracy. Ideally, new methods perform best subset selection faster than existing optimal methods but with comparable accuracy, or, being more accurate than methods of comparable computational speed. Here, we propose a novel continuous optimization method that identifies a solution path, a small set of models of varying size, that consists of candidates for the best subset in linear regression. Our method turns out to be very fast, making the best subset selection possible when the number of features is well in excess of thousands. Because of the outstanding overall performance, framing the best subset selection challenge as a continuous optimization problem opens new research directions for feature extraction for a large variety of regression models.