Miracle-dz/UniFAR-FTUs huggingface dataset:
Antithymocyte globulin versus basiliximab induction for kidney transplantation in elderly patients: matched analysis within the Korean multicentric registry

Background Basiliximab (BSX) and antithymocyte globulins (ATGs), are two major immunosuppressive agents commonly used as induction therapy for kidney transplant (KT) recipients. The superiority of ATG over BSX has not been well established, especially in elderly KT recipients with low immunological risk. Methods A total of 847 elderly (≥60 years old), low-risk KT patients in the Korean Organ Transplantation Registry were propensity score-matched at a 1:2 ratio and compared according to ATG or BSX induction therapy. The primary outcome was patient and graft survival and biopsy-proven acute cellular rejection. The secondary outcome was graft function, BK virus nephropathy, infection, cancer, new-onset diabetes mellitus after transplantation (NODAT), and delayed graft function. Results In total, 165 patients in the ATG group were matched with 298 patients in the BSX group with average ages of 64.3 and 64.2 years, respectively. During a follow-up of 28.5 ± 10.4 months, the cumulative probabilities of death-censored graft failure at 3 years posttransplantation were 1.3% and 1.4% in ATG and BSX groups, respectively, without a significant difference (p = 0.72). The cumulative probability of NODAT at 3 years posttransplantation was significantly higher in the BSX group (35.6% vs. 21.6%, p = 0.02). The median tacrolimus trough level was significantly lower at 6 months after KT in the ATG group (5.7 ng/mL vs. 6.4 ng/mL, p = 0.001). There were no differences in the other evaluated outcomes. Conclusion Compared with BSX, in elderly, low-risk KT patients, ATG reduced tacrolimus and steroid requirements without differences in all-cause mortality, rejection, or infection, resulting in a reduced NODAT incidence.
Are Recent SISR Techniques Suitable for Industrial Applications at Low Magnification?

In recent years, many deep-network-based super-resolution techniques have been proposed and have achieved impressive results for 2<inline-formula><tex-math notation="LaTeX">${\times }$</tex-math></inline-formula> and higher magnification factors. However, lower magnification factors encountered in some industrial applications have not received special attention, such as 720P-to-1080P (1.5<inline-formula><tex-math notation="LaTeX">${\times }$</tex-math></inline-formula> magnification). Compared to traditional 2<inline-formula><tex-math notation="LaTeX">${\times }$</tex-math></inline-formula> or higher magnification factors, these lower magnifications are much simpler, but reconstructions of high-definition images are time-consuming and computationally complex. Hence, in this paper, a fast image upsampling method is designed specifically for industrial applications at low magnification. In the proposed method, edge and nonedge areas are first distinguished and then reconstructed via different fast approaches. For the edge area, a local edge pattern encoding-based method is presented to recover sharp edges. For the nonedge area, a global iterative reconstruction with texture constraint is utilized. Moreover, some acceleration strategies are also presented to further reduce the complexity. The experimental results demonstrate that the proposed method can obtain performance comparable to that of some state-of-the-art methods for 720P-to-1080P magnification, but the computational cost is much lower.
Strained Lattice Gold-Copper Alloy Nanoparticles for Efficient Carbon Dioxide Electroreduction

Electrocatalytic conversion of carbon dioxide (CO2) into specific renewable fuels is an attractive way to mitigate the greenhouse effect and solve the energy crisis. AunCu100-n/C alloy nanoparticles (AunCu100−n/C NPs) with tunable compositions, a highly active crystal plane and a strained lattice were synthesized by the thermal solvent co-reduction method. Transmission electron microscopy (TEM) and X-ray diffraction (XRD) results show that AunCu100−n/C catalysts display a subtle lattice strain and dominant (111) crystal plane, which can be adjusted by the alloy composition. Electrochemical results show that AunCu100−n/C alloy catalysts for CO2 reduction display high catalytic activity; in particular, the Faradaic efficiency of Au75Cu25/C is up to 92.6% for CO at −0.7 V (vs. the reversible hydrogen electrode), which is related to lattice shrinkage and the active facet. This research provides a new strategy with which to design strong and active nanoalloy catalysts with lattice mismatch and main active surfaces for CO2 reduction reaction.
Physically Distancing Humans With An App for That: Physically Distancing Mangement Technologies

As COVID-19 continues to create havoc in everyday lives, the need to limit the spread of the virus remains a challenge, even with advances in medical knowledge and patient care, and the promise of a vaccine. Furthermore, COVID-19 is one in a recent series of airborne diseases, and probably not the last one, given the ongoing encroachment of humans into animal habitat. This paper proposes that a key challenge related to virus containment is physical containment. That is, maintaining safe distance from individuals who might have been exposed to the virus. A physical distancing app is proposed, and the challenges associated with its development and use identified.
Strategy Dynamics and the Theory of the Firm: Homage to Richard Rumelt

Richard Rumelt helped pioneer many key ideas in the field of strategic management, including how the ownership of unique bundles of resources determines competitive outcomes, how isolating mechanisms protect rent streams, and how entrepreneurship drives the firm’s choices of markets and resources. He chose not to build these insights into an integrated framework. However, his perspective on strategy and his emphasis on coherent actions for the firm is both complementary to and connected with the concept of organizational capabilities. The dynamic capabilities framework builds on Rumelt’s work and can serve as a basis for advancing the strategic theory of the firm on which Rumelt began work in the 1980s.
AGENT BASED APPROACH TO FORM LOGICAL COMMERCIAL FORMATION FLIGHTS

SUMMARY The ex ist ing tr end in air t ranspor tat ion growt h, c lear ly shows t hat av iat ion indust r ies need t o pr of oundly look at “f or mat ion f lights ” in a mor e ef f ic ient manner and w it hout complex c omput at ions. T his work descr ibes a new ef f ic ient Logic to accept or r eject a poss ible f or mat ion among all available. T he appr oac h cons iders eac h airplane as an agents t hat “sees ” t he c urr ent t raff ic env ironment and then s elects t he bes t “Act ion” to sat isfy its des ir ed object iv es. The logic, alt hough s imple, c ons iders the loc at ion and t ime t o join a f or mat ion or t o cr eate one; and t he pos it ion to leav e t he or iginal f or mat ion. D iff er e nt M at hemat ical model hav e been inv est igat ed t o f ind -out w hic h one is mor e r eliable f or fas t -t ime s imulat ions. T he pr eliminary r esults ar e pr omis ing; es pec ially for a f or mat ion of any tw o airplanes of diff er ent types. As a pr act ic al measur e, w e hav e als o i nv est igat ed t he ef fects of det er minis t ic as well as non -det er minist ic f light delays on f or ming a s uccessful for mat ion.
Pengetahuan Tentang Program Merdeka Belajar Kampus Merdeka dan Minat Mengikuti Program Merdeka Belajar Kampus Merdeka Studi Empirik Terhadap Mahasiswa Fakultas Ilmu Pengetahuan Budaya, Universitas Al Azhar Indonesia

The MBKM program was first launched in early 2020 to provide opportunities for students to be active outside the campus. I took part in this program. A number of socialization activities were carried out to provide knowledge about what and how the MBKM program was. In two years, 235 UAI students have participated in 8 MBKM programs. This number can increase as the number of students who know and understand the program increases, as well as their knowledge of the benefits and risks of the program they are interested in. By utilizing Prospect Theory (Tversky and Kahneman, 1992), this study examines the relationship between the knowledge that students have about the MBKM program, both its benefits and risks, their degree of interest in the program, and the choice of the type of program they are interested in. The results indicate that students who have a higher perception of the potential benefits that can be achieved from MBKM activities are expected to have a higher interest in participating in, and recommending the MBKM program to their colleagues with the same risk perception; and vice versa.Keywords – By utilizing the Prospect Theory of Tversky and Kahneman, 1992, By utilizing the Prospect Theory of Tversky and Kahneman, 1992 Benefits, knowledge, prospects, risks, theory
Broadband and high gain circularly polarised truncated corner square patch metasurface antenna using aperture CPW feed

Broadband and the high gain circularly polarised antenna are designed in a single-layered planar substrate. An array of 3 × 3 truncated corner square patches are designed as a metasurface antenna on one side of the substrate and the metasurface antenna is fed by a stub-loaded uniform aperture CPW feed on another side of the substrate. In the metasurface antenna, the size of the central patch is increased for improving the bandwidth of impedance bandwidth and 3 dB axial ratio. Furthermore, the amount of truncation is reduced in the patches surrounding the central patch to enhance the bandwidth of impedance bandwidth and 3 dB axial ratio bandwidth. The designed metasurface antenna has achieved an impedance bandwidth of 38.2% (4.5–6.63 GHz) with an axial ratio bandwidth of 13% (5.0–5.7 GHz). Moreover, the antenna has a peak gain of 10.36dBic. The simulation and measurement results are compared.
Small Molecules and Immunotherapy Agents for Enhancing Radiotherapy in Glioblastoma

Glioblastoma (GBM) is an aggressive primary brain tumor that is associated with a poor prognosis and quality of life. The standard of care has changed minimally over the past two decades and currently consists of surgery followed by radiotherapy (RT), concomitant and adjuvant temozolomide, and tumor treating fields (TTF). Factors such as tumor hypoxia and the presence of glioma stem cells contribute to the radioresistant nature of GBM. In this review, we discuss the current treatment modalities, mechanisms of radioresistance, and studies that have evaluated promising radiosensitizers. Specifically, we highlight small molecules and immunotherapy agents that have been studied in conjunction with RT in clinical trials. Recent preclinical studies involving GBM radiosensitizers are also discussed.
Documenting the Contribution of People to Successful Business Model Implementation:

The absence of people (employees) from the business model literature is at odds with their pivotal contribution to the value creation, delivery and capture process. As a resource that management is continually challenged to grow, their success in doing so has been identified as an outcome falling within the scope of Integrated Reporting, an approach currently touted as the new corporate reporting. This short paper suggests a number of employee attributes that might be documented in such reports.
MARVAir: Meteorology Augmented Residual-Based Visual Approach for Crowdsourcing Air Quality Inference

Air pollution has become a prominent problem in citizens’ everyday life. Since the weather stations are not densely distributed, it is difficult to get fine-grained particulate matter <inline-formula> <tex-math notation="LaTeX">$< 2.5~\mu \text{m}$ </tex-math></inline-formula> (PM<sub>2.5</sub>) data. We propose Meteorology Augmented Residual-Based Visual Approach for Crowdsourcing Air Quality Inference (<italic>MARVAir</italic>) to address limitations of traditional PM<sub>2.5</sub> prediction mechanism. First, we use crowdsourcing and spider-bots to fetch visual and meteorological dataset, respectively. Second, a residual neural network (ResNet)-based visual core is designed to learn the image data, and a 1-D convolutional neural network (CNN)-based meteorology core is deployed to tune the inference. Besides, we use decision-level fusion mechanism to unite the submodels and provide precise yet everywhere available fine-grained PM<sub>2.5</sub> inference. In addition, cloud-side model training is also proposed to restrict local energy consumption. Evaluation on dataset collected at eight sites over nearly two years suggests that <italic>MARVAir</italic> achieves a precision of 98.8%, a recall of 99.0%, and an <inline-formula> <tex-math notation="LaTeX">$F1$ </tex-math></inline-formula>-score of 98.9% under various air conditions, which notably exceed baseline solutions.
Peningkatan Kemampuan Tanggung Jawab, Berpikir Kritis, Pengelolaan dan Pemahaman Skema Keuangan Siswa Semanggi Digital Marketing Semarang

Kaum muda perlu memiliki kemampuan literasi keuangan yang baik karena hal ini menghindarkan masalah keuangan yang masih sangat sering terjadi. Banyak kaum muda karena kurangnya pengetahuan tentang literasi keuangan terjebak pada hutang yang tidak bisa diperhitungkan dengan baik sehingga menggaggu masalah pengelolaan keuangan mereka. Kegiatan pengabdian kepada masyarakat diperlukan untuk dilaksanakan untuk kaum muda, dalam pelaksanaannya metode yang digunakan adalah observasi, sosialisasi dan pendaftaran peserta, pelaksanaan pelatihan, dan capaian luaran. Berdasar penjelasan dari beberapa rujukan mengenai literasi keuangan, tanggung jawab, berpikir kritis, mengelola keuangan dan memahami skema keuangan adalah hal sangat penting untuk ditingkatkan utamanya bagi kaum muda yang masih dalam keadaan perlu untuk dibimbing dan dibina. Melalui pelatihan financial life skills ini, kaum muda mendapatkan kemampuan untuk menyiapkan diri menghadapi dunia kerja dan dapat mengelola keuangan pribadi yang pada akhirnya akan meningkatkan kualitas hidup mereka dan menciptakan peluang ekonomi baru bagi mereka baik dalam bekerja atau menjadi wiraswasta.
Wall roughness influence on the efficiency characteristics of centrifugal pump.

Many different machines are developed in industry and in terms of energy conversion, their efficiency is one of the most important parameters. A lot of theoretical, experimental and numerical analyses are done in the development process in order to obtain required characteristics. Computational fluid dynamics (CFD) analyses are a very important part of the development process. To obtain accurate results it is important to pay attention to geometry definition, usage appropriate numerical model, quality of the computational grid, realistic boundary conditions and all of the other parameters regarding fluid and solid material properties. A very important issue is usually the correct selection of the turbulence model. In most CFD analyses, only smooth surface is taken into account without considering any wall roughness. Besides the usage of different physical and mathematical models and all required parameters, the wetted surface roughness can also be one of the important origins of the numerical results inaccuracy. In the paper, the analysis of the influence of different parameters such as the sandgrain equivalent parameter is presented. The influence of y+ on the accuracy of the flow analysis with different absolute roughness of the surfaces is also analyzed. For basic relations, the flow in simple geometries like flow over flat plate and flow in circular pipe has been analyzed. The conclusions of the preliminary research work are used in the case of efficiency prediction of centrifugal pump with rough walls. The final numerical results are compared with the experimental ones and show better agreement in comparison with the flow over smooth walls.
COGNITIVE LOAD AND QUESTION ASKING – THE CASE OF PROSPECTIVE MATHEMATICS TEACHERS COPING WITH HISTORICAL TEXTS

"In this study, we examined aspects relating to the impact of integrating question-asking activities and providing answers to these questions while reading historical mathematical texts on prospective mathematics teachers' self-reported cognitive load. The research group included two classes of 20 students each (experimental and control groups). The experimental group was instructed to ask questions while coping with the texts, whereas the control group received no special instructions. The experimental group participants were asked to think aloud while coping with the texts and audio record themselves. These recordings were transcribed into written protocols. In addition, both groups had to respond to a self-esteem index questionnaire in which they had to report the level of difficulty they experienced as an indicator of their cognitive load. The data was analyzed using quantitative and qualitative methods. Two main observations were obtained: the first is that question-asking reduces cognitive load, and the second is that question-asking supports the assimilation of new information up to a specific limit, depending on the gap between existing knowledge and new information. "
An Active Damping Control Method for Reduced DC-Link Capacitance PMSM Drives With Low Line Inductance

The power density can be improved and the system cost can be saved in the reduced dc-link capacitance motor drive system. The line inductance can also be diminished to reduce the system volume further. In previous research works, the active damping control methods mainly concentrated on the drive system equipped with a larger line inductor. In this article, a dc-link voltage estimation feedback-based active damping method is proposed to suppress the grid current harmonics and improve the drive system stability with low line inductance. The dc-link voltage ripple caused by the LC resonance is analyzed to evaluate the direct dc-link voltage feedback-based active damping control method. To improve the damping performance, the resonant component of the dc-link voltage caused by the LC resonance could be obtained through the grid current to establish the feedback control loop. The sampling delay should be compensated to improve the control performance. The stability of the drive system is evaluated by the Nyquist plots of the impedance model, and the grid current is also analyzed, which could satisfy the harmonic requirements of IEC-61000-3-2. Experimental results are performed to verify the effectiveness of the proposed method.
A Novel Remaining Useful Life Prediction Method for Capacity Diving Lithium-Ion Batteries

To be prepared for the capacity diving phenomena in future capacity deterioration, a hybrid method for predicting the remaining useful life (RUL) of lithium-ion batteries (LIBs) is proposed. First, a novel empirical degradation model is proposed in this paper to improve the generalization applicability and accuracy of the algorithm. A particle filter (PF) algorithm is then implemented to generate the original error series using prognostic results. Next, a discrete wavelet transform (DWT) algorithm is designed to decompose and reconstruct the original error series to improve the data validity by reducing the local noise distribution information. A relatively less approximate component is selected as the reconstructed error series, which preserves the primary evolutionary information. Finally, to make full use of the information contained in the PF algorithm’s prognosis results, the support vector regression (SVR) algorithm is utilized to correct the PF prognosis results. The results indicate that long–short-term deterioration progress and RUL prediction tasks can both benefit from significant performance improvements.
Deep Learning-Based Rice Leaf Diseases Detection Using Yolov5

The Rice crop in Agriculture field is playing an important role in economy of Pakistan and fulfilling the needs of living hood of human beings. The rice leaf faces several diseases like Bacterial Bligh, Brown Spot, Blast and Tungro. This research attempts to create a simple and best model for Rice leaf disease detection using deep learning model Yolov5. The model has been upgraded to v5 which is the latest version of Yolo. The performance and accuracy of object detection using Yolov5 is better than Yolov3 and Yolov4 models. This model is able to differentiate and successfully detect the rice leaf diseases. The Rice leaf images Dataset is downloaded from Kaggle website, the dataset contains 400 images of leaf infected by disease. This paper uses Google colab platform to train, validate and test the model for Rice Leaf disease detection. All necessary steps to be implemented, the rice leaf disease are detected and fully described. The developed model utilize epochs: 100. The experimental results show that the deep learning model created with 100 epochs has shown the best performance with precision, recall, and mAP value of 1.00, 0.94, and 0.62, respectively.
Transvaginal Ultrasound vs. Magnetic Resonance Imaging (MRI) Value in Endometriosis Diagnosis

(1) Background: Endometriosis is a widespread gynecological condition that causes chronic pelvic discomfort, dysmenorrhea, infertility, and impaired quality of life in women of reproductive age. Clinical examination, transvaginal ultrasonography (TVS), and magnetic resonance imaging (MRI) are significant preoperative non-invasive diagnosis procedures for the accurate assessment of endometriosis. Although TVS is used as the primary line for diagnosis, MRI is commonly utilized to achieve a better anatomical overview of the entire pelvic organs. The aim of this systematic review article is to thoroughly summarize the research on various endometriosis diagnosis methods that are less invasive. (2) Methods: To find relevant studies, we examined electronic databases, such as MEDLINE/PubMed, Cochrane, and Google Scholar, choosing 70 papers as references. (3) Results: The findings indicate that various approaches can contribute to diagnosis in different ways, depending on the type of endometriosis. For patients suspected of having deep pelvic endometriosis, transvaginal sonography should be the first line of diagnosis. Endometriosis cysts are better diagnosed with TVS, whereas torus, uterosacral ligaments, intestine, and bladder endometriosis lesions are best diagnosed using MRI. When it comes to detecting intestine or rectal nodules, as well as rectovaginal septum nodules, MRI should be the imaging tool of choice. (4) Conclusions: When diagnosing DE (deep infiltrative endometriosis), the examiner’s experience is the most important criterion to consider. In the diagnosis of endometriosis, expert-guided TVS is more accurate than routine pelvic ultrasound, especially in the deep infiltrative form. For optimal treatment and surgical planning, accurate preoperative deep infiltrative endometriosis diagnosis is essential, especially because it requires a multidisciplinary approach.
Competing hypotheses on the Samuelson effect in futures markets

ABSTRACT Using data of 12 commodity futures traded on three major futures exchanges in U.S., we find that about 55% of the agricultural futures contracts exhibit the Samuelson effect, about 30% for energy futures contracts, but only about 20% for metal and financial futures contracts. The proposed approach also enables us to take the unprecedented step of directly comparing explanatory power of the state variable hypothesis and the mean reversion hypothesis over the Samuelson effect. The result overall suggests that the mean reversion hypothesis can better explain the Samuelson effect.
Gun Safety: A Call to License Arms

The culture of safety that has developed for automobiles has been no mistake. Decades of advocacy from a plurality of voices were required to implement the intrinsic (e.g. seatbelts and airbags) and regulatory (e.g. speed limits and blood alcohol concentration limits) safety measures that have reduced the rate of vehicular fatalities by 90% since 1925. 1 The gradual change occurred through grassroots organizing, political action and increased industry standardization. This public health achievement creates a helpful case for car safety that can be applied to the current debate on guns.