Miracle-dz/UniFAR-FTUs huggingface dataset:
An Auto Chip Package Surface Defect Detection Based on Deep Learning

Defect detection in chip packaging is a crucial step to ensure product quality and reliability. Traditional methods typically employ image-processing techniques for defect detection during the chip manufacturing process. However, these solutions require manual feature extraction and have limited adaptability to complex scenarios. Thus, deep-learning (DL)-based methods have received widespread attention. Nevertheless, they may fail to achieve the requirements of real-time and high accuracy, and effective datasets are still missing. In this article, we construct a new chip package surface defect detection dataset, which contains 2919 images and four common defect types. To our knowledge, it is the only dataset for simultaneous detection of multiple chips. Also, we propose a real-time chip package surface defect detection method based on the you only look once version 7 (YOLOv7) model to solve the challenge of detecting small targets. In particular, we utilize $k$ -means++ to recluster the anchor frames, merge the convolutional block attention module (CBAM) attention mechanism and receptive field block (RFB) structure, as well as replace traditional nonmaximum suppression (NMS) with our newly proposed confidence propagation cluster (CP-Cluster) to further increase detection accuracy and result confidence. Finally, we evaluate our method by performing many ablation experiments on the dataset we created. The experimental results demonstrate that compared to the original YOLOv7, the proposed method improves the mean average precision@0.5 (mAP@0.5) by 1.39%, the speed of detection by 21.6%, reduces the amount of computation by 17.7%, and the number of parameters by 66.4%, respectively. This proves the superiority and practicality of the proposed method.
Nanolayered Structures and Nanohybrids Based on a Ternary System Co/Ti/Zn for Production of Photo-Active Nanocomposites and Purification of Water Using Light

Water pollution has emerged as a major challenge for the scientific community because of the rapid expansion of the population and the industrial sector in the world. The current study focuses on introducing a new track for designing new optical nanocomposites for purifying water in addition to providing a new additive for building new nanohybrids. These targets were achieved through building a ternary system of Co/Ti/Zn nanocomposites and nanolayered structures. The Co/Ti/Zn nanolayered structures were prepared and intercalated by different kinds of organic acids: monocarboxylic and dicarboxylic acids. Long chains of organic acids were used to construct series of organic–inorganic nanohybrids. X-ray diffraction, thermal analyses, Fourier Transform Infrared spectroscopy, and scanning electron microscopy confirmed the formation of nanolayered structures and nanohybrids. The optical properties of the nanolayered structure showed that the Co/Ti/Zn LDH became photo-active compared with the usual Al/Zn LDH because of the reduction in the band gap energy from 5.3 eV to 3.3 eV. After thermal treatment, a highly photo-active nanocomposite was produced through observing more reduction for the band gap energy to become 2.8 eV. In addition, the dye of Acid Green 1 completely decomposed and converted to water and carbon dioxide during 17 min of UV radiation by the dual Co/Ti-doped zinc oxide nanocomposite. In addition, the kinetic study confirmed that the high optical activity of the dual Co/Ti-doped zinc oxide nanocomposite accelerated the degradation of the green dyes. Finally, from these results it could be concluded that designing effective nanocomposite for purification of water was accomplished through converting 2D nanolayered structures to a 3D porous structure of Ni/Ti/Zn nanocomposites. In addition, a new additive was achieved for heterostructured hybrids through building new Co/Ti/Zn/organic nanohybrids.
Soils and runaway global warming: Terra incognita

Increasingly, the expression “global warming” is being replaced in the news media by the much more ominous one of “runaway global warming” (e.g., Hileman 2005; Brown 2006), auguring more or less explicitly the possible extinction of the human race in the not too distant future. Often, no real justification is offered for the added “runaway” qualifier, other than the fact that things are rapidly getting worse. This perception is reinforced daily, for example by reports of ever more abnormal weather patterns all over the world or by shocking images of huge chunks of the ice cap in Antarctica collapsing into the ocean at a rate far more rapid than was expected even a couple of years ago. Yet, with few exceptions, newspapers and news programs on radio and television rarely delve into in-depth analyses of the situation. One has to turn to specialized scholarly journals to find detailed (but technical and therefore not widely accessible) accounts of the processes that seem to make global warming accelerate at an alarming pace. In these accounts, soil-related processes are more and more in the spotlight (e.g., Smith et al. 1998; Kirschbaum 2006; A …
Regulating Cryptocurrencies: A Supervised Machine Learning Approach to De-Anonymizing the Bitcoin Blockchain

Abstract Bitcoin is a cryptocurrency whose transactions are recorded on a distributed, openly accessible ledger. On the Bitcoin Blockchain, an owning entity’s real-world identity is hidden behind a pseudonym, a so-called address. Therefore, Bitcoin is widely assumed to provide a high degree of anonymity, which is a driver for its frequent use for illicit activities. This paper presents a novel approach for de-anonymizing the Bitcoin Blockchain by using Supervised Machine Learning to predict the type of yet-unidentified entities. We utilized a sample of 957 entities (with ≈385 million transactions), whose identity and type had been revealed, as training set data and built classifiers differentiating among 12 categories. Our main finding is that we can indeed predict the type of a yet-unidentified entity. Using the Gradient Boosting algorithm with default parameters, we achieve a mean cross-validation accuracy of 80.42% and F1-score of ≈79.64%. We show two examples, one where we predict on a set of 22 clusters that are suspected to be related to cybercriminal activities, and another where we classify 153,293 clusters to provide an estimation of the activity on the Bitcoin ecosystem. We discuss the potential applications of our method for organizational regulation and compliance, societal implications, outline study limitations, and propose future research directions. A prototype implementation of our method for organizational use is included in the appendix.
Cǎtre O Strategie Inteligentǎ Pentru Agriculturǎ Din Perspectiva Schimbǎrilor Climatice (Towards a Climate-Smart Agriculture Strategy)

Romanian Abstract: Schimbările climatice reprezintǎ ameninţări tot mai mari pentruagricultură, ducând la scǎderea randamentelor de producţie si la cresterea presiunilorasupra resurselor de apă si a calităţii solului. Pe de altǎ parte, in contextul tendinţelordemografice asteptate, cererea de alimente si culturi agricole la nivel global impune ocrestere a producţiei agricole. Date fiind aceste douǎ tendinţe divergente, pentru a sprijinidezvoltarea sectorului agricol se impune o abordare strategică, care sǎ ţinǎ seama, pe de oparte, de efectele schimbǎrilor climatice, prin presiuni tot mai mari asupra resurselorprimare - de apǎ si sol si, pe de altǎ parte, de cresterea cererii de produse agricole sialimentare, legatǎ de perspectivele cresterii populaţiei la nivel global.English Abstract: Climate change represents an increasing threat to agriculture, by diminishing production yields and increasing pressure on water resources and soil quality. On the other hand, increasing demand for food and crops related to demographic projections, will ask for higher agricultural production. Given these two divergent trends, agricultural sector development should be supported by a strategic approach, that will take into account, on one hand, the climate change effects of increasing pressure on primary resources - water and soil and, on the other hand, the increasing demand for food and agricultural products, related to the prospects for global population growth.
A Comparative Analysis Of The Regional Development Agencies In Europe And Turkey

The Regional Development Agencies were put into effect in Turkey within 26 agencies with the Law number 5449 that was passed in 2006 after European countries as a foundation highlighting the understanding of territorialisation, localization and competition. The aim of the study is to compare the recently founded Development Agencies in Turkey with the long-established system in Europe. Moreover in this study, the concepts of region and regional development are described and the origination conditions of development agencies in Turkey and in the world are explained shortly. The structure of the development agencies in European countries, especially in those in the European Union (EU), which have been active for a long time, is compared with that of the development agencies in Turkey from many perspectives. This study reveals that the development agencies in Turkey and Europe show differences in terms of their aims, legal positions, and supervisions, whereas, they show similarities in terms of their founders, general characteristics, organizational structures, fields of activities, staff employment, financial sources and project centers.
Mri segmentation and the quantification of white matter lesions

Magnetic Resonance Imaging (MRI) has rapidly become one of the most important diagnostic tools available to clinicians. This popularity is mainly due to the facts that MRI has no known side-effects, that it is non-invasive, and that it has a very high resolving power for soft tissues. As such, it is extremely valuable for in-vivo studies of the human brain. An additional advantage of MRI is its multispectral character, which makes it possible to generate images of the same physical space with different spectral signatures. The interpretation of MRI data is currently done in a predominantly visual and qualitative fashion. However, the increasing amount of data generated by modern MR scanners and the clinical demand for accurate, reproducible, and quantitative data analysis promote the development of computer-aided techniques. An artificial neural network based image analysis system has been developed and tested, focused on the quantification of so-called white matter lesions in the human brain. Early in the course of this research it became clear that spatial intensity variations, often present in MRI data, hamper the use of classical pattern recognition techniques. Several methods for the correction of this artifact and studies showing the reliability of the proposed segmentation technique are presented.
Soil and water conservation behaviors within the upper Mississippi River Basin

After seven decades of conservation programs that have consumed billions o f dollars of economic resources and vast quantities of human resources, soil erosion and subsequent degradation o f water resources remain serious environmental issues within the United States (US). Millions of tons of chemical-rich topsoil are lost each year from agricultural land, which contributes to environmental degradation. Environmental degradation associated with soil erosion is frequently classified into two broad categories of damages, termed on-site and off-site costs. Some of the most significant on-site costs of soil erosion are as follows: loss of farm income, loss of resale value o f land resources, reduced output of agricultural products, reduced aesthetic quality of land resources, and loss of agricultural fertilizers and pesticides (Napier, et al, 2000a; Lovejoy and Napier, 1986). On-site costs are primarily borne by landowners and often serve as motivators for land owner-operators to take corrective action to prevent further environmenta1 degradation. Some of the most significant off-site damages are as follows: loss of wildlife habitat, loss of recreation opportunities due to water pollution …
DEMAND SUBSTITUTION BETWEEN TANKERS OF DIFFERENT SIZES

On suppose que des modifications en ce qui concerne les conditions du marche pour des groupes de navires petroliers de toute dimension induisent des reactions en chaine a travers le marche de fret des petroliers. Presentation d'un modele pour analyser des elasticites directes et a prix croise dans les transports du petrole pour des navires petroliers de differentes dimensions. Analyse des variations des taux de fret et des correlations entre ces taux. Les elasticites sont estimees en employant a la fois la forme reduite et la forme structurale du modele
Hyperparameter Tuning on Graph Neural Network for the Classification of SARS-CoV-2 Inhibitors

COVID-19 is caused by the SARS-CoV-2 virus, which results in a range of symptoms, from mild to severe, and can lead to fatalities. As of October 2023, WHO has recorded 771 cases of COVID-19 globally. Various efforts have been made to control the spread of the virus, including vaccination, isolation measures, and intensive medical care. The emergence of new SARS-CoV-2 variants has led to the ongoing evolution of virus transmission. Continued research is essential to understand this virus and develop strategies to address the pandemic. Inhibitors of SARS-CoV-2 play a crucial role in the vaccine development process. Inhibitors can impede the virus's development, helping reduce disease severity and control the pandemic. The classification of inhibitors is expected to serve as a foundation for selecting compounds that can be developed into vaccines. This research develops a Graph Neural Network model for inhibitor classification and uses the random search method for hyperparameter tuning. Graph Neural Networks are chosen due to their excellent performance in modelling graph data. This study demonstrates the success of hyperparameter tuning in improving the performance of the Graph Neural Network for accurate classification of SARS-CoV-2 inhibitors.
Upwelling to Outflowing Oxygen Ions at Auroral Latitudes during Quiet Times: Exploiting a New Satellite Database

The mechanisms by which thermal O + escapes from the top of the ionosphere and into the magnetosphere are not fully understood even with 30 years of active research. This thesis introduces a new database, builds a simulation framework around a thermospheric model and exploits these tools to gain new insights into the study of O + ion outflows. A dynamic auroral boundary identification system is developed using Defense Meteorological Satellite Program (DMSP) spacecraft observations at 850 km to build a database characterizing the oxygen source region. This database resolves the ambiguity of the expansion and contraction of the auroral zone. Mining this new dataset, new understanding is revealed. We describe the statistical trajectory of the cleft ion fountain return flows over the polar cap as a function of activity and the orientation of the interplanetary magnetic field y-component. A substantial peak in upward moving O + in the morning hours is discovered. Using published high altitude data we demonstrate that between 850 and 6000 km altitude, O + is energized predominantly through transverse heating; and acceleration in this altitude region is relatively more important in the cusp than at midnight. We compare data with a thermospheric model to study the effects of solar irradiance, electron precipitation and neutral wind on the distribution of upward O + at auroral latitudes. EUV irradiance is shown to play a dominant role in establishing a dawn-focused source population of upwelling O + that is responsible for a pre-noon feature in escaping O + fluxes. This feature has been corroborated by observations on platforms including the Dynamics Explorer 1 (DE-1), Polar, and Fast Auroral Snapshot SnapshoT (FAST) spacecraft. During quiet times our analysis shows that the neutral wind is more important than electron precipitation in establishing the dayside O + upwelling distribution. Electron precipitation is found to play a relatively modest role in controlling dayside, and a critical role in controlling nightside, upwelling O + . This thesis provides a new database, and insights into the study of oxygen ion outflows during quiet times. These results and tools will be essential for researchers working on topics involving magnetosphere-ionosphere interactions.
Toxic Environmental Risk Factors for Alzheimer’s Disease: A Systematic Review

A l z h e i m e r ’s d i s e a s e ( A D ) i s a n i r r e v e r s i b l e degenerative brain disorder that affects memory, intellectual ability, and other cognitive functions. AD is the most common form of dementia and a leading cause of morbidity and mortality globally. The 2015 World Alzheimer Report showed that approximately 47 million people have AD or related dementias worldwide. As populations continue to age, the number of persons living with dementia, including AD, is expected to rise to over 130 million by 2050 this increase will particularly affect countries with a fastgrowing elderly population. Individuals aged 60 years and above are projected to constitute a fifth of the world population over the next three-four decades, and more than 75% will be living in Asia, Latin America or Africa. Despite the current epidemiology of AD and its economic and public health impacts, the cause of the disease remains unknown.
Upper First and Second Molar Pulp Chamber Endodontic Anatomy Evaluation According to a Recent Classification: A Cone Beam Computed Tomography Study

(1) The possibility of knowing information about the anatomy in advance, in particular the arrangement of the endodontic system, is crucial for successful treatment and for avoiding complications during endodontic therapy; the aim was to find a correlation between a minimally invasive and less stressful endodontic access on Ni-Ti rotary instruments, but which allows correct vision and identification of anatomical reference points, simplifying the typologies based on the shape of the pulp chamber in coronal three-dimensional exam views. (2) Based on the inclusion criteria, 104 maxillary molars (52 maxillary first molars and 52 maxillary second molars) were included in the study after 26 Cone Beam Computed Tomography (CBCT) acquisitions (from 15 males and 11 females). And linear measurements were taken with the CBCT-dedicated software for subsequent analysis. (3) The results of the present study show data similar to those already published about this topic. Pawar and Singh’s simplified classification actually seems to offer a schematic way of classification that includes almost all of the cases that have been analyzed. (4) The use of a diagnostic examination with a wide Field of View (FOV) and low radiation dose represents an exam capable of obtaining a lot of clinical information for endodontic treatment. Nevertheless, the endodontic anatomy of the upper second molar represents a major challenge for the clinician due to its complexity both in canal shape and in ramification.
Self-Decoupled Linear and Planar MIMO Microstrip Patch Antenna Arrays Operating in the Fundamental TM01 Mode

The H-plane coupled multi-input multi-output (MIMO) rectangular microstrip patch antenna (MPA) array is investigated. To ensure compact size as well as good radiation performance, the excited MPA is designed to operate in the single fundamental TM01 mode. On the other hand, due to the near-field coupling effect, the TM01 mode and the adjacent TM11 mode are simultaneously excited in the coupled MPA. The superposed field of the two coupled modes forms a null-field region at the position of feeding probe, generating an intrinsic coupling dip with low <inline-formula> <tex-math notation="LaTeX">$\vert \text{S}_{21}\vert $ </tex-math></inline-formula> above the resonance frequency of TM01 mode. To make use of this intrinsic coupling dip, the decoupling band is moved downward to overlap with the impedance passband by simply truncating two rectangular corners from the rectangular MPA. A self-decoupled convex MPA array is thus achieved without requiring any additional decoupling structure. This self-decoupling method is also applicable to the E-plane coupled MPA array, and more importantly, it is extendable to a large-scale planar MIMO array, showing great universality. For validation, a <inline-formula> <tex-math notation="LaTeX">$2\times2$ </tex-math></inline-formula> MPA array is simulated, fabricated, and measured. A 4% usable bandwidth with <inline-formula> <tex-math notation="LaTeX">$\vert \text{S}_{ii}\vert < -10$ </tex-math></inline-formula> dB and <inline-formula> <tex-math notation="LaTeX">$\vert \text{S}_{ij}\vert < -20$ </tex-math></inline-formula> dB is achieved, and the maximum isolation is over 50 dB.
The CROP-04 seismic profile. Interpretation and structural setting of the Agropoli-Barletta Geotraverse

The CROP-04 seismic profile, acquired between 1989 and 1990 and reprocessed by the Geophysical Group of the Earth Sciences Department of the University of Milan, has been interpreted by adopting the usual techniques integrated with the use of a work station. Four reflectors have been recognized and then calibrated on the basis of the exploration wells available in the region- (1) the top of the Apennine Platform; (2) the top of Lagonegro-Irpinia flysch sequence or imbricate; (3) the top of the Apulian Platform and (4) the base of the carbonate sequence. Many of these reflectors are recognized as the trace of the overthrust planes, as well. Thanks to the reflectors' geometric setting, it has been possible to recognize the following features: in the western part of the profile, the Apennine Platform flat-ramp system (Cilento) displaced together with the Permo-Triassic substratum, develops a duplex, the M. Soprano unit overtrhrusts over the Alburno unit; in the central part, the Inner Apulian Platform forms a possible antiformal stack under Mt. Marzano and a series of upthrusts deepening under the Ofanto Valley, where the Lagonegro-Irpinia flysch imbricate shows its greatest thickness. To the east, the complex including the Apennine Platform, Lagonegro-Irpinia Flysch imbricate and the Inner Apulian Platform, forms an accretionary wedge that ovethrusts over the Outer Apulian Platform, that is mainly affected by extensional tectonics and abruptly plunges westward, under the allochthonous complex. The CROP-04 seismic profile does not allow the deep structural setting to be outlined. For the time being, it can be concluded that along the Agropoli-Barletta Geotraverse, three sectors - western, axial and eastern - have been recognized, the first two belonging to the range domain and the third to the foreland.