Miracle-dz/UniFAR-FTUs huggingface dataset:
Prediction of Neoadjuvant Chemoradiotherapy Response in Rectal Cancer Patients Using Harmonized Radiomics of Multcenter 18F-FDG-PET Image

Simple Summary Neoadjuvant chemotherapy is the standard treatment for locally advanced rectal cancer. Preoperative chemoradiotherapy yields clinically significant tumor regression; while some patients exhibit a minimal response, others exhibit a complete pathologic response. We developed deep learning and machine learning models to predict chemoradiotherapy response across external tests using multicenter data. The machine learning model, which used harmonized image features extracted from 18F-FDG PET, showed higher performance and demonstrated reproducibility through external tests compared to the deep learning models using 18F-FDG PET images. Our study highlights the feasibility of predicting the chemoradiotherapy response of individual patients using non-invasive and reliable image feature values. Abstract We developed machine and deep learning models to predict chemoradiotherapy in rectal cancer using 18F-FDG PET images and harmonized image features extracted from 18F-FDG PET/CT images. Patients diagnosed with pathologic T-stage III rectal cancer with a tumor size > 2 cm were treated with neoadjuvant chemoradiotherapy. Patients with rectal cancer were divided into an internal dataset (n = 116) and an external dataset obtained from a separate institution (n = 40), which were used in the model. AUC was calculated to select image features associated with radiochemotherapy response. In the external test, the machine-learning signature extracted from 18F-FDG PET image features achieved the highest accuracy and AUC value of 0.875 and 0.896. The harmonized first-order radiomics model had a higher efficiency with accuracy and an AUC of 0.771 than the second-order model in the external test. The deep learning model using the balanced dataset showed an accuracy of 0.867 in the internal test but an accuracy of 0.557 in the external test. Deep-learning models using 18F-FDG PET images must be harmonized to demonstrate reproducibility with external data. Harmonized 18F-FDG PET image features as an element of machine learning could help predict chemoradiotherapy responses in external tests with reproducibility.
Acidity Quantification and Structure Analysis of Amide-AlCl3 Liquid Coordination Complexes for C4 Alkylation Catalysis

Liquid coordination complexes (LCCs), which are formed between metal halides and donor molecules, represent promising catalysts. Six amide-AlCl3 LCCs were successfully synthesized, followed by their characterization through NMR, Raman, and UV-visible spectroscopy. The acidity of these LCCs was quantified by performing computational modelling of fluoride ion affinities (FIA) and experimental Gutmann–Beckett measurements. Spectroscopic analysis indicated bidentate coordination between amide ligands and Al, which induced asymmetric splitting of Al2Cl6 into diverse ions such as [AlCl2L2]+, [AlCl4]−, [AlCl3L], and [Al2Cl6L]. The computed FIA was found to align well with the experimental acidity trends, thereby confirming the proposed structure of the LCC. In the alkylation tests, the LCC with a high acidity demonstrated an increase in the yields of C5-C7 alkylates. These results provide an in-depth understanding of the tuneable structures of amide-AlCl3 LCCs. The acidity of LCCs can be controlled by tuning the ratio of the organic ligand to AlCl3, which allows bidentate coordination to facilitate asymmetric splitting of Al2Cl6. The LCCs demonstrate a high degree of potential as versatile and sustainable acid catalysts in alkylation reactions. These findings may advance the foundational knowledge of LCCs for the purpose of targeted acid catalyst design.
Vulnerability and Risk Assessment of Artificial Recharge of the Oanob Aquifer, Namibia

Water plays a vital role in human life. It is therefore necessary to take care of the resources available. However, the water is not equally distributed over the world causing water scarcity in some countries. One of these countries is Namibia, the driest country in sub-Saharan Africa, where reasonable amounts of drinking water are sometimes located far away from major human settlements and where the cost of transporting it is high. The increasing water demand in Windhoek, the capital city of Namibia, has brought forward the plans of using the Oanob Aquifer as a possible water source. The aquifer, located approximately 90 kilometres south of Windhoek, lies within the alluvials of the Oanob River just south of the town of Rehoboth. Both towns consider using the water from the aquifer as an additional water supply. The aquifer is currently 24 % full and for the aquifer to be viable as a water supply, artificial infiltration is necessary. The potential of artificially recharging the aquifer could then provide Rehoboth and possibly Windhoek with spare water. The aim of the project was to do a vulnerability and risk assessment of the Oanob Aquifer to investigate the possibility of artificial infiltration and to recommend a sustainable solution for additional water supply to Windhoek to continue supplying Rehoboth. A Geographical Information System software called ArcGIS 9 was used to perform the vulnerability assessment. The assessment shows that most of the aquifer is highly vulnerable to contamination due to its alluvium content and protective measures have to be implemented to protect the aquifer and the artificial recharge scheme. This is more particularly in the upstream compartment, where there are higher water levels and where the clay content is assumed to be relatively low. After the vulnerability assessment was performed, the identified pollution sources on the aquifer and in its vicinity were rated according to the risk they pose to the groundwater. Together with the vulnerability map this was used to perform a risk assessment that showed that the highest risks are in the upstream compartment, due to the high concentration of hazardous sources and its high vulnerability. The assessments conclude that artificial recharge of the Oanob Aquifer is a good option for Windhoek as well as for Rehoboth to extend their security of water supply, though protective measures are necessary to prevent the aquifer from being polluted.
Ignimbrites of Amazonis Planitia region of Mars

A series of postulated ignimbrite units is mapped in the Amazonis, Memnonia, and Aeolis quadrangles of Mars. The units cover about 2.2×106 km2 within a broad but discontinuous and irregular belt trending east-west along the highland-lowland boundary. The ignimbrites overlie parts of the western and southern aureole materials of Olympus Mons but are embayed in places by the lava plains of the lowlands. Stratigraphic relations between the basalt flows from the Tharsis Montes region and the ignimbrites are not clearly defined; crater counts suggest that the younger ignimbrites postdate the lava flows. Crater counts per square kilometer for the ignimbrites range from 7.29±1.95×10−4 to 6.36±2.01×10−5 for craters larger than 1 km in diameter. The ignimbrite materials form thick (≥100 m), extensive, relatively flat sheets that are smooth to grooved or gently undulating. Grooved surfaces appear to be yardangs and, in most places, are not alined with prevailing wind directions. The seven mapped ignimbrite units are characterized by morphologic expression, stratigraphic position, and crater counts. Similarities to ignimbrites in the Pancake Range of central Nevada include (1) rounded patches of smooth, high-albedo, nonwelded material superposed on jointed, low-albedo, welded material, (2) local complementary joint sets in welded materials, and (3) thick flow sheets of great areal extent that follow but subdue underlying topography. Four major eruptive centers occur in areas where units are thickest and where a dominant, NNW-SSE structural trend is expressed locally by unit margins, elongate collapse features, and normal faulting. A minimum volume of 3.85×106 km3 for the deposits has been calculated from thickness estimates based on shadow measurements and crater rim height relations.
The Expressions of Sodium Chloride Cotransporter (NCC mRNAs) in the Kidney Hypertensive Rats

The present study hypothesized that chronic administration of candesartan will not only improve the sensitivity of alpha-adrenergic receptors to adrenergic agonists but also modulate the expression of angiotensin receptors (AT1a) and sodium chloride cotransporter (NCC) mRNAs. Animals were divided into four groups WKY control; WKY received candesartan (WKY-CST, 10 mg/kg), SHR control, and SHR received candesartan (SHR-CST). Plasma, urine samples, and mean arterial pressure (MAP) were taken on days 0, 21, and 28. Acute studies determined the renal vasoconstrictor actions of Ang II, noradrenaline (NA), phenylephrine (PE), and methoxamine (ME). The overall mean drops in renal cortical blood perfusion (RCBP) to NA, PE, ME, and Ang II were significantly increased in WKY-CST and SHR-CST when compared to the respective control. Expression of AT1a mRNA in the kidney of WKY-CST and SHR-CST were increased 11 folds and 8 folds respectively when compared to internal control (β-actin). Expression of NCC MRNA in the kidney of WKY-CST and SHR-CST were 10 folds and 6 folds respectively when compared to internal control. Candesartan restores the functional responsiveness of alpha-adrenergic receptors in normal and spontaneously hypertensive rats by alleviating mean arterial pressure, enhancing renal cortical blood perfusion, and increasing the functional capabilities of the kidney by modulating renal tubular and glomerular functions. Secondly, chronic administrations of candesartan in SHR regulated the expression of AT1a mRNA and NCC mRNA in SHR rat kidneys when compared to SHR control rats.
High-Speed, Low-Voltage Programmable/Erasable Flexible Two-Bit Organic Transistor Nonvolatile Memories Based on Ultraviolet-Ozone Treated Terpolymer Ferroelectric Gate

Organic field-effect transistor nonvolatile memory (OFET-NVM) is an indispensable element for flexible and wearable electronics. The emerging multi-bit OFET-NVMs propose an effective strategy to further multiply the storage capacity. However, they have still suffered serious bottleneck issues of high programming/erasing (P/E) voltage and slow P/E speed. In this letter, we demonstrate a facile method to resolve the both bottlenecks, and investigate the relevant mechanisms. Our flexible OFET-NVMs exhibit excellent 2-bit memory features, with a fast P/E speed of $5~\mu \text{s}$ , low P/E voltages of ±15 V, highly reliable endurance, highly stable retention, and good mechanical durability. This work paves the way toward the development of next-generation high-speed, high-capacity flexible memory.
Cultural Participation Patterns: Evidence from the Spanish Time Use Survey

We explore cultural participation in Spain by doing an empirical exercise with the data of the Encuesta de Empleo del Tiempo 2002-2003 for Spain (TUS), a multi-member household time use dataset. We use information on individual time allocation for a surveyed day and for cultural attendance for the previous last four weeks. Taking benefit of that information, we are able of discussing both resource allocation issues, as well as observed choices. First, we take benefit of the individual diaries to describe time allocated to each type of cultural activity and estimate models that explain that allocation at the individual level. We estimate fractional logit models. Second, we use the variables that measure social and cultural participation in the last 4 weeks to study the determinants of cultural attendance for a wide set of activities. We estimate models for count data that allow characterizing the observed behaviour as the mixing of heterogeneous subpopulations. Last, we interpret the findings and discuss future research.
Influence of Artificial Recharge on Groundwater Quality

In order to study the effect of artificial recharge on the groundwater quality,the evolvement law of groundwater quality in Western Daqing City was firstly studied by using inverse geochemistry simulation method.The results showed that the groundwater quality was affected by dissolve-precipitation of aquifer minerals,alternate adsorption of cation and redox function.The dominative mine-rals in aquifer are calcite,dolomite,halite,fluorite,gypsum,hematite,siderite,pyrolusite,carbon dioxide and cation exchanger.Based on the above work,a water-rock interaction case among Nenjiang River water,groundwater of Xi-waterwork and aquifer minerals in western Daqing City was studied through forward geochemistry simulation method.The results showed that the TDS of mixing water will decrease,the more surface water quantity in mixing water,the lower TDS of mixing water.The artificial recharge water will not lead to catastrophe or decrease of water quality in aquifer,and it will improve water quality in aquifer to some extent.
DESENVOLVIMENTO DE RECURSOS DIDÁTICOS PARA A DIVULGAÇÃO CIENTÍFICA DA ENERGIA SOLAR

Resumo . O avanço tecnológico na sociedade atual promove o crescimento do consumo energético global e, consequentemente, a necessidade de se desenvolver fontes alternativas de energias limpas e sustentáveis. Dentre estas, destacam-se os recentes investimentos e o grande potencial da energia solar fotovoltaica no Brasil. Neste contexto, o objetivo do presente estudo consiste em desenvolver recursos didáticos e ações de divulgação científica para conscientização sobre o funcionamento e a promoção do conhecimento relativo à energia solar fotovoltaica, por meio do ensino lúdico, interativo e intuitivo da temática para crianças e adolescentes em idade escolar. Estas ações e recursos didáticos instrucionais são gratuitos e promovem a inclusão tecnológica e social através com a divulgação científica da energia solar. Ações desta natureza não foram observadas na literatura
Dynamic analysis of malwarae intrusion in mobile devices using Adaboost Algorithm, KNN and SVM base classifiers

Cyber security is becoming more worrisome; malware is spreading by the day through proliferation and distribution of variants of known family signatures using obfuscation techniques. Mobile devices components such as central processing unit, memory, battery life, executable files and operating systems are constantly being attacked and rendered unusable. Attack agents are specifically evading detection, damaging mobile devices’ executive files, stealing information, surcharging users for SMS sent and received without their knowledge or permission, and freezing applications for a ransom among others. This research work is keying into the fight against malware intrusion by designing and developing an intrusion detection system (IDS) using ensemble learning, boosting. Adaboost algorithm trains base classifiers (KNN and SVM) using network security laboratory-knowledge discovery in databases (NSL-KDD) dataset to build a more formidable classifier that will detect malware intrusion in mobile devices using cloud technology. The result obtained in this combination technique is 91.4% accurate with a bias (standard deviation) as low as 2.7%.
Integrating Computer Vision in Exosuits for Adaptive Support and Reduced Muscle Strain in Industrial Environments

Exosuits are wearable technologies that improve physical capabilities and mobility providing support during various activities. Although primarily intended for medical rehabilitation, there is growing interest in utilizing exosuits in industrial environments to prevent work-related musculoskeletal disorders (WMSDs) by ensuring continuous joints support. However, achieving synchronization between the exosuit and human motion, as well as effectively controlling interactions with the surroundings, presents ongoing challenges. The integration of computer vision techniques, particularly object recognition algorithms, can greatly assist exosuits in understanding the user's environment and adapting their behaviour accordingly. To address this issue, we have developed a control strategy for a soft exosuit that employs computer vision to collaboratively offer tailored assistance to the elbow, alleviating joint stress during interactions with objects of various natures and weights. We conducted a study to assess the effectiveness of the integrated system, which merges object recognition and gravity compensation within a built-in structure of the robotic exosuit. The findings confirmed that the suggested solution notably minimized muscle strain during dynamic activities, exhibiting a consistent correlation with the mass of the object being lifted, namely reducing by 45% and 54% respectively the Biceps activity while lifting the MW and HW compared to the 32% of the “Dynamic Arm”. The intention of this contribution is to pave the way for incorporating the vision algorithm, thus enabling a more efficient interaction between the user and the exosuit itself. This includes adapting the control strategy to account for variations in environmental dynamics.
THE IMPACT OF ORGANIZATIONAL MOBILITY PREFERENCE ON COMPULSORY CITIZENSHIP BEHAVIOR

Based on the social exchange theory and the boundaryless career perspective, this study used a questionnaire method to examine the mechanism by which employees' preferences for organizational mobility influence their obligatory citizenship behavior. The results showed that: (1) employees’ organizational mobility preference positively predicted their compulsory citizenship behavior; (2) employees’ preference for organizational mobility had negative and positive effects on employees’ relational and transactional psychological contracts, respectively; (3) both relational and transactional psychological contracts partially mediated the influence of employees’ preferences for organizational mobility on their compulsory citizenship behavior, with the mediation effect of transactional psychological contract being stronger; (4) organizational development support positively moderated the mediation effect of transactional psychological contract, but the moderating effect of organizational development support on the relationship between employees’ preferences for organizational mobility and relational psychological contract was not significant.
Math Anxiety, Achievement and Perceptions of Same-Ethnic Peers in Math Class

Using multiple linear regression analysis, this research explores racially and ethnically diverse students’ feelings of math anxiety, how these beliefs shape their achievement in the subject, and whether students’ math anxiety and performance in mathematics vary based on students’ gender, race/ethnicity, and math level. Moreover, this study investigated the potential protective functions of perceiving a high proportion of same-ethnic peers in math class for buffering against the detrimental effects of high math anxiety on achievement. Results showed that when African American students reported a high level of math anxiety, their math grades were lower when they also perceived there to be a high proportion of same-ethnic peers in their math course compared to White students with similar levels of math anxiety and perceptions of same-ethnic peers. These results suggest that the effects of classroom same-ethnic representation for students’ academic outcomes are more nuanced than labeling it as a “protective” factor. Other contextual factors may influence the relationship between math anxiety, perceived same-ethnic representation in math class, and achievement and should be explored in future research.
Pathways to develop state capacity in a weak state: the sub-national state of Bihar in India

ABSTRACT This article aims to unravel how a weak state develops state capacity – an aspect hitherto ignored in mainstream literature. This is a study of a sub-national case of Bihar in India. Historically, Bihar is considered a weak state, lacking state capacity. Yet, improvements have occurred in recent decades. By profiling two areas of improved outcomes: infrastructure (roads and bridges) and welfare (distribution of bicycles to school-going girls), the article argues that the improvements are the outcome of the political and bureaucratic elite’s ideas and political will. The case of Bihar shows that the rationalities within a state depend on social learning, puzzling, and powering, having a powerful impact on policy paradigms even in weak states.
The Turbidite Problem

Abstract The turbidity current hypothesis has met with much support as well as severe criticism. Dogmatic statements in support of this hypothesis are not uncommon in the literature and a clear distinction between fact and inference is not always made. First developed as an explanation for the origin of submarine canyons, the turbidity current hypothesis was later applied to explain the deposition of ancient flysch-type sediments as well as recent deep-sea deposits of alternating coarse and fine layers. Though a turbidity current origin for these two facies has not yet been demonstrated beyond reasonable doubt, diagnostic features of the one are commonly used to prove such an origin for the other. Such circular reasoning is unwarranted and data from both facies should be kept strictly separated. Evidence to support the turbidity current hypothesis comes from three areas: ancient flysch-type sediments; Recent deep-sea deposits; and experimental turbidity currents. Careful study of this evidence shows so ma.
Analysis of discretionary lane-changing behaviours of autonomous vehicles based on real-world data

23 With the deployment of autonomous vehicles, a transition period where autonomous vehicles 24 share the roads with human-driven vehicles is inevitable where the discretionary lane-changing 25 behaviors of autonomous vehicles can be safety-critical. This study aims to quantify the impact 26 of discretionary lane-changing behaviors on following vehicles in the target lane using a real-27 world dataset. This study uses the Waymo Open Dataset to identify the differences between the 28 discretionary lane-changing maneuvers of autonomous vehicles and human-driven vehicles and 29 compare their impacts on the driving volatility metrics. Then, the block maxima model is applied 30 to estimate the crash risks. Finally, the multivariate adaptive regression splines model is adopted 31 to model gap acceptance behaviors of autonomous vehicles and human-driven vehicles. Results 32 show that compared to human-driven vehicle discretionary lane-changing, autonomous vehicle 33 discretionary lane-changing leads to lower speeds and yaw rate volatility and smaller 34 acceleration rates of the following vehicles. Further, the block maxima model reveals that the 35 crash risk in the autonomous vehicle discretionary lane-changing events is half of that in the 36 human-driven vehicle discretionary lane-changing events. In addition, autonomous vehicles and 37 human-driven vehicles show different lead gap acceptance behaviors, according to the results of 38 multivariate adaptive regression splines. The findings highlight the benefits of mixing 39 autonomous vehicles in traffic flow and guide the improvement of autonomous vehicle 40 controllers. 41
A Model of Place Image Influences on Geographical: Business Expansion Decisions to Foreign Locations

This paper presents a brief overview of how the concept of place image (otherwise called destination image by some authors) influences management decisions to expand to new business districts in countries outside their current geographies of business operation. A theoretical model explaining this relationship is introduced following the review of existing theoretical literature. Findings from the study reveal the conceptualization of 38 hypothetical statements, which captures the linkages between place image and geographical business expansion (GBE). This model together with its hypotheses makes an attempt to expand current discourse on place image and place branding by providing insights into issues that drive managerial decisions to invest in specific locations outside their original domain of operations. Importantly, the new hypotheses (conceptualized in this study) provide an opportunity for an elaborate research in the near future.