Miracle-dz/UniFAR-FTUs huggingface dataset:
An analysis of small-signal source-body resistance effect on RF MOSFETs for low-cost system-on-chip (SoC) applications

In this paper, we demonstrate a comprehensive analysis of small-signal source-body resistance (R/sub sb/) effect on the RF performances of RF MOSFETs for low-cost system-on-chip (SoC) applications for the first time. Our results show that for RF MOSFETs, both the kink phenomena of S/sub 11/ and S/sub 22/ become more obscure as reverse body bias (V/sub B/) increases due to the decrease of transconductance (g/sub m/). In addition, an increase of source-body spacing enhances both the kink phenomena of S/sub 11/ and S/sub 22/, but deteriorates the current-gain cut-off frequency (f/sub T/), maximum oscillation frequency (f/sub MAX/), and RF noise and power performances due to the increase of R/sub sb/ of the devices. Analytical formulas are derived to explain the kink phenomena of S/sub 11/ and S/sub 22/, and to explain why increasing R/sub sb/ leads to a reduction of equivalent substrate resistance R/sub sub/, or worse f/sub T/, f/sub MAX/, and RF noise performances of the devices. The present analyzes enable RF engineers to understand the S-parameters, noise parameters, and power performances of RF MOSFETs more deeply, and hence are helpful for them to optimize the layout of MOSFETs and to create a fully scalable RF CMOS model for SoC applications.
Component Detection with Deep Learning A review

Object detection is a computerized technology-related Computer vision and image processing. It is a technique that allows us to identify and locate objects in an image or video. With the help of this technology the identification and localization of objects or any component can be simplified, object detection can be used to count objects in a scene and determine and track their precise locations, all while accurately labeling them. Object detection algorithms typically leverage machine learning or deep learning to produce meaningful results. The goal of object detection is to replicate this intelligence using a computer. Object detection can be done more accurately using certain algorithms. OpenCV which is a python library that functions mainly on computer vision, Yolo is the most efficient real-time algorithm which is used to effectively detect an object. In deep learning, CNN TensorFlow Keras is the algorithms used to accurately locate and identify objects.
Risks for Using FeCl3 Under a Submerged Condition, and Different Water Management to Reduce Uptake of Antimony and Cadmium in a Rice Plant

Soil pollution by multiple metal(loid)s is a common problem, and it is not easy to synchronously reduce their uptake in crops. Compounds containing iron (Fe) are often used to efficiently remediate soil metal(loid) pollution; however, its associated risks did not receive much attention especially under unsuitable soil water conditions. Pot experiments were set up using an antimony (Sb) and cadmium (Cd) co-contaminated soil treated with a continued submergence condition plus 5, 10, or 20 mg kg−1 FeCl3 (Experiment I), or treated with different water management including submergence, intermittent irrigation, and dry farming (Experiment II). Our results showed that the continued submergence resulted in excessive accumulation of arsenic (As) in different tissues of rice plants even if the soil As background concentration is low. High soil moisture content increased the available concentrations of Sb and As, but reduced that of Cd in rhizosphere soils, which was in line with their concentrations in different tissues of rice plants (Experiment II). Under a continued submergence condition, FeCl3 significantly stimulated As concentration in the shoots, roots (excluded Fe20 treatment), and husks, but reduced it in the grains. FeCl3 reduced Sb concentration only in the roots and grains, and reduced Cd concentration only in the husks, suggesting a limited efficiency of FeCl3 to reduce Cd uptake under a submergence condition. In this study, the dynamic changes of As, Sb, and Cd concentrations in soil solution, their available concentrations in rhizosphere soils, their accumulation in root iron/manganese plaques, and the relationships among the above parameters were also discussed. We suggested that if FeCl3 would be used to remediate the contaminated soils by Sb and Cd, dry farming for a short time is needed to avoid As accumulation, and intermittent irrigation is a potential choice to avoid the excessive accumulation of As, Sb, and Cd in the edible parts of rice plants.
Genotypic and Phenotypic Characterization of Novel Sequence Types of Carbapenem-Resistant Acinetobacter baumannii, With Heterogeneous Resistance Determinants and Targeted Variations in Efflux Operons

Acinetobacter baumannii has emerged as one of the dominant nosocomial human pathogens associated with high morbidity and mortality globally. Increased incidences of carbapenem-resistant A. baumannii (CRAB) have resulted in an enormous socioeconomic burden on health-care systems. Here, we report the genotypic and phenotypic characterization of novel ST1816 and ST128 variants in A. baumannii strains belonging to International clone II (GC2) with capsule types KL1:OCL8 and KL3:OCL1d from India. Sequence analysis revealed the presence of diverse virulome and resistome in these clinical strains, in addition to islands, prophages, and resistance genes. The oxacillinase blaOXA–23detected in the genomic island also highlighted the coexistence of blaOXA–66/blaOXA–98, blaADC73/blaADC–3, and blaTEM–1D in their mobile scaffolds, which is alarming. Together with these resistance-determining enzymes, multidrug efflux transporters also harbored substitutions, with increased expression in CRAB strains. The hotspot mutations in colistin resistance-conferring operons, PmrAB, LpxACD, and AdeRS, were additionally confirmed. Phenotype microarray analysis indicated that multidrug-resistant strains A. baumannii DR2 and A. baumannii AB067 preferred a range of antimicrobial compounds as their substrates relative to the other. To our knowledge, this is the first comprehensive report on the characterization of A. baumannii variants ST1816 and ST128, with different genetic makeup and genome organization. The occurrence of CRAB infections worldwide is a severe threat to available limited therapeutic options; hence, continued surveillance to monitor the emergence and dissemination of such novel ST variants in A. baumannii is imperative.
Influence of Axial Load and a 45-Degree Flexion Head Position on Cervical Spinal Stiffness in Healthy Young Adults

Background: Neck pain is a major cause of disability worldwide. Poor neck posture such as using a smartphone or work-related additional cervical axial load, such headgear of aviators, can cause neck pain. This study aimed at investigating the role of head posture or additional axial load on spinal stiffness, a proxy measure to assess cervical motor control. Methods: The posterior-to-anterior cervical spinal stiffness of 49 young healthy male military employees [mean (SD) age 20 ± 1 years] was measured in two head positions: neutral and 45-degree flexed head position and two loading conditions: with and without additional 3 kg axial load. Each test condition comprised three trials. Measurements were taken at three cervical locations, i.e., spinous processes C2 and C7 and mid-cervical (MC). Results: Cervical spinal stiffness measurements showed good reliability in all test conditions. There was a significant three-way interaction between location × head position × load [F(2, 576) = 9.305, p < 0.001]. Significant two-way interactions were found between measurement locations × loading [F(2, 576) = 15.688, p < 0.001] and measurement locations × head position [F(2, 576) = 9.263, p < 0.001]. There was no significant interaction between loading × head position [F(1, 576) = 0.692, p = 0.406]. Post hoc analysis showed reduction of stiffness in all three measurement locations in flexion position. There was a decrease in stiffness in C2 with loading, increase in stiffness in C7 and no change in MC. Discussion: A flexed head posture leading to decreased stiffness of the cervical spine might contribute to neck pain, especially if the posture is prolonged and static, such as is the case with smartphone users. Regarding the additional load, stiffness decreased high cervical and increased low cervical. There was no change mid cervical. The lower spinal stiffness at the high cervical spine might be caused by capsular ligament laxity due to the buckling effect. At the lower cervical spine, the buckling effect seems to be less dominant, because the proximity to the ribs and sternum provide additional stiffness.
Analysis of the Relevance of the Ultrasonographic Features of Papillary Thyroid Carcinoma and Cervical Lymph Node Metastasis on Conventional and Contrast-Enhanced Ultrasonography

Background Preoperative prediction of lymph node metastases has a major impact on prognosis and recurrence for patients with papillary thyroid carcinoma (PTC). Thyroid ultrasonography is the preferred inspection to guide the appropriate diagnostic procedure. Purpose To investigate the relationship between PTC and cervical lymph node metastasis (CLNM, including central and lateral LNM) using both conventional ultrasound (US) and contrast-enhanced ultrasound (CEUS). Material and Methods Our study retrospectively analyzed 379 patients diagnosed with PTC confirmed by surgical pathology at our hospital who underwent US and CEUS examinations from October 2016 to March 2021. Individuals were divided into two groups: the lymph node metastasis group and the nonmetastasis group. The relationship between US and CEUS characteristics of PTC and CLNM was analyzed. Univariate and multivariable logistic regression methods were used to identify the high-risk factors and established a nomogram to predict CLNM in PTC. Furthermore, we explore the frequency of CLNM at each nodal level in PTC patients. Results Univariate analysis indicated that there were significant differences in gender, age, tumor size, microcalcification, contact with the adjacent capsule, multifocality, capsule integrity and enhancement patterns in CEUS between the lymph node metastasis group and the nonmetastasis group (all P<0.05). Multivariate regression analysis showed that tumor size ≥1 cm, age ≤45 years, multifocality, and contact range of the adjacent capsule >50% were independent risk factors for CLNM in PTC, which determined the nomogram. The diagnostic model had an area under the curve (AUC) of 0.756 (95% confidence interval, 0.707-0.805). And calibration plot analysis shown that clinical utility of the nomogram. In 162 PTC patients, the metastatic rates of cervical lymph nodes at levels I-VI were 1.9%, 15.4%, 35.2%, 34.6%, 15.4%, 82.1%, and the difference was statistically significant (P<0.001). Conclusion Our study indicated that the characteristics of PTC on ultrasonography and CEUS can be used to predict CLNM as a useful tool. Preoperative analysis of ultrasonographical features has important value for predicting CLNM in PTCs. The risk of CLNM is greater when tumor size ≥1 cm, age ≤45 years, multifocality, contact range of the adjacent capsule >50% are present.
Mechanobiology of Microvascular Function and Structure in Health and Disease: Focus on the Coronary Circulation

The coronary microvasculature plays a key role in regulating the tight coupling between myocardial perfusion and myocardial oxygen demand across a wide range of cardiac activity. Short-term regulation of coronary blood flow in response to metabolic stimuli is achieved via adjustment of vascular diameter in different segments of the microvasculature in conjunction with mechanical forces eliciting myogenic and flow-mediated vasodilation. In contrast, chronic adjustments in flow regulation also involve microvascular structural modifications, termed remodeling. Vascular remodeling encompasses changes in microvascular diameter and/or density being largely modulated by mechanical forces acting on the endothelium and vascular smooth muscle cells. Whereas in recent years, substantial knowledge has been gathered regarding the molecular mechanisms controlling microvascular tone and how these are altered in various diseases, the structural adaptations in response to pathologic situations are less well understood. In this article, we review the factors involved in coronary microvascular functional and structural alterations in obstructive and non-obstructive coronary artery disease and the molecular mechanisms involved therein with a focus on mechanobiology. Cardiovascular risk factors including metabolic dysregulation, hypercholesterolemia, hypertension and aging have been shown to induce microvascular (endothelial) dysfunction and vascular remodeling. Additionally, alterations in biomechanical forces produced by a coronary artery stenosis are associated with microvascular functional and structural alterations. Future studies should be directed at further unraveling the mechanisms underlying the coronary microvascular functional and structural alterations in disease; a deeper understanding of these mechanisms is critical for the identification of potential new targets for the treatment of ischemic heart disease.
High performance current regulator for a field-oriented controlled induction motor drive

A novel strategy of current regulation of a field-oriented controlled induction motor using a gate turn-off thyristor (GTO) inverter is proposed which is based on multivariable state feedback control with an integrator. The controller is designed by the pole placement technique of multivariable system regulation theory. Feedforward control is included in the control laws to improve transient responses. For the full state feedback control, the rotor flux is estimated with a reduced-order state observer. A good steady-state performance is obtained by means of an integral compensation, and fast transient response is also feasible since the required voltage is directly calculated from the feedforward control. Space voltage vector pulse width modulation is adopted as a switching strategy. A variable modulation scheme is presented which is changed from three-phase to two-phase modulation in the high modulation range, which gives lower current ripple over the whole operating range. <<ETX>>
An AC-AC inverter with build-in power factor correction soft-switching and a unified controller

This paper presents a full bridge AC-AC inverter for high frequency power distribution system with power factor correction stage controlled by a unified controller. The proposed inverter has the following features: (1) load independent output voltage with constant frequency and very low total harmonic distortion; (2) soft switching of the full bridge switches for a wide range of input voltage and load conditions; (3) simple control and cost effectiveness for the power factor correction stage; (4) minimum DC bus voltage in the worst case. Operating principles and performance characteristics are presented, and guidance to design the converter is given. Experimental results of a 90-265 V/sub AC/ input, 30 V/sub AC/ output at 100 kHz, 250 W prototype are given to verify the thoretical analysis and computer simulations.
Modelling and Simulation of An Isolated Power Generating System Using Doubly Fed Induction Generators

There are many load centres that are isolated from the main utility grid. Some of them are remote villages, islands, ships, etc. They require isolated electric supply by means of stand-alone electrical generators to provide for their local electrical loads. The proposed model is used for standalone system where the power is fed directly to the local loads for the applications where the connectivity to the grid is not possible. The system can also be made to work in combination with grid and local loads . In Islanding mode the generator supplies the local loads during the light load and during heavy load condition, the excess power is absorbed/ supplied by battery energy storage system (BESS) which is connected parallel to dc link capacitor. A three phase load, independent wind energy conversion system is employed using DFIG operated at variable speeds for supplying the power to local loads and also perform the function of load levelling and harmonic elimination.
Factors Affecting Air Traffic Controller Workload: Multivariate Analysis Based on Simulation Modeling of Controller Workload

Airspace capacity in a high-density air traffic network is determined by controller workload. Controller workload is primarily affected by the features of the air traffic and air traffic control (ATC) sector. Factors that affect controller workload are examined by, first, a review of the literature on this subject and then a multivariate analysis of the data obtained from simulations of a model of air traffic controller workload. This model, the European Airspace Model (EAM), has been widely used in European airspace planning. The results from simulations of five very different areas of European airspace are analyzed. In particular, the results of principal components analysis and factor analysis provide a valuable insight into the aircraft profile factors affecting controller workload.
The implementation of enterprise resource planning systems in small-medium manufacturing enterprises in South-East Queensland: a case study approach

This paper examines the implementation of ERP systems in small/medium-sized enterprises in South East Queensland, Australia. Nine case studies were conducted to determine factors for success or failure in the implementations, Key success factors identified included cross-functional team approaches, organisational experience of similar scale IT or organisational change projects, and 'deep' understanding of the key issues relating to ERP implementations. Failure factors identified included top-down or consultant driven implementations, IT department driven implementations, or implementations where the ERP is seen as a quick technological fix to problems within the operation of the firm, rather than as a strategic investment.
Minimizing conditional value‐at‐risk under a modified basestock policy

Consider a single‐product, make‐to‐stock, risk‐averse company that manages its finished goods inventory by a basestock policy. Item demand is modeled as a Poisson process, and unit production time is modeled as an exponential random variable. Annual cost is equal to the sum over one year of the inventory‐holding and back‐ordering costs. The company wants to minimize the annual cost conditional value‐at‐risk by an appropriate basestock selection called the optimal basestock. After offering evidence that the optimal basestock is analytically intractable, we derive a closed‐form approximation of the optimal basestock. In two independent simulation experiments, we found that the average penalty for using the approximation is less than 1%; we believe this accuracy would be acceptable for practical applications. Leveraging the approximation's accuracy and simplicity, we establish several results that may serve as predictors of the company's appropriate basestock adjustments to changes in operational, economic, and risk aversion parameters. We illustrate how our research results were successfully applied in a Fortune 10 energy company. We extend the problem setting in two different directions to widen the applicability of our research results.
Estimation Method of the Future Age Structure of Small Area based on the Mesh-based Population Census Data

(1)都市計画における人口予測 従来から、都市計画のさまざまな検討に量的なイメージ を与えるために、将来人口が不可欠な基礎情報と位置づけ られ、都市計画策定プロセスの早い段階で、将来人口が設 定されてきた 。 しかし、都市全体でみれば安定的な人口 増加トレンドが観察されていたことから精緻な予測手法の 必要性は弱く、過去のトレンドの単純な延長をベースとし て、必要に応じて地域産業の動向や大規模開発などの影響 を主観的に加味するという簡易な方法がとられてきた。 ま た小地区別の分布への関心も弱く、上述の全体値を近年の 比率で固定的に配分した値が用いられてきた。 都市全体で 整備すべき施設の量を地域的に配分するという目的のため には、このような概略的な値でも十分であったともいえる。 (2)少子高齢化に伴う新しい課題 しかし、少子高齢化が進み、都市全体の人口も停滞から 減少へと転じる中で、高齢化が先行的に進み人口の減少が 継続する地区が現れてきた。 実際、多くの都市ではモータ リゼーションに取り残された都心部において、人口減少と 高齢化が進行しており、商業機能などの活力低下の主要な 原因となっている 。 このような地区においては、需要の 減少に対応して都市施設の整理、統合を進め、施設の維持 管理費用を削減することが必要となる。 また人口構成の変 化に合わせ、学校施設を別の用途に転用することが必要と なってきた。 さらに、阪神淡路大震災や新潟中越地震後の 避難生活が物語っているように、各地区において助けを必 要とする人々に対応して、それを支えることのできる年齢 階層の人々が居住していることが、コミュニティーレベル での「共助」にとって重要であることが指摘されている 。 地区ごとの災害への対応力を高め、都市施設の整理・統 合計画を立案するためには、地区ごとの将来の人口を、年 齢構成とともに予測することが必要となる。 そして、地区 のコミュニティや、都市施設、都市サービスを維持するた めに、予測された人口が不十分なものであれば、地区を支 える年齢層を誘致、保持することを積極的に検討していく ことが重要となる。 (3)本研究の目的 本研究は、地区ごとの将来の年齢階層別人口を予測する 方法を提案することを目的とする。 すでに整備、公開され ている国勢調査地域メッシュデータの中には年齢階層別人 口の情報が含まれているため、年齢階層別生残率を用いて 自然増減を予測することは可能であるが、小地区の社会増 減の予測方法は確立していない。 小地区になれば、コウホート(同時出生集団)ごとの社会 増減率は安定的でないことや、データ量が膨大になること から、市町村レベルの予測で使われているコウホート変化 率法を適用することが難しいためである。 そこで本研究で は、コウホートごとの変化量を因子分析により集約し、よ り少ない要素にまとめて安定的に捉えるとともに、その因 子得点の時間的推移を説明するベクトル自己回帰モデルを 作成することにより、入手可能なデータを最大限に活用し て社会増減の予測を行う方法を提案する。 (4)本論文の構成 以下、2. では既存の人口予測手法を概観し、小地区へ の適用上の問題点を指摘する。 3. では本研究で提案する 人口予測手法の説明を行う。 4. では広島市とその周辺の 626個の4次メッシュ(1辺約500m)に予測手法を適用す る。 5. では、本研究の成果と今後の課題を述べる。 33. 国勢調査メッシュデータに基づく地区の将来人口構成予測手法
FirmPot: A Framework for Intelligent-Interaction Honeypots Using Firmware of IoT Devices

IoT honeypots that mimic the behavior of IoT devices for threat analysis are becoming increasingly important. Existing honeypot systems use devices with a specific version of firmware installed to monitor cyber attacks. However, honeypots frequently receive requests targeting devices and firmware that are different from themselves. When honeypots return an error response to such a request, the attack is terminated, and the monitoring fails.To solve this problem, we introduce FirmPot, a framework that automatically generates intelligent-interaction honeypots using firmware. This framework has a firmware emulator optimized for honeypot generation and learns the behavior of embedded applications by using machine learning. The generated honeypots continue to interact with attackers by a mechanism that returns the best from the emulated responses to the attack request instead of an error response.We experimented on embedded web applications of wireless routers based on the open-source OpenWrt. As a result, our framework generated honeypots that mimicked the embedded web applications of eight vendors and ten different CPU architectures. Furthermore, our approach to the interaction improved the session length with attackers compared to existing ones.
Protocol-Based Deep Intrusion Detection for DoS and DDoS Attacks Using UNSW-NB15 and Bot-IoT Data-Sets

Since its inception, the Internet of Things (IoT) has witnessed mushroom growth as a breakthrough technology. In a nutshell, IoT is the integration of devices and data such that processes are automated and centralized to a certain extent. IoT is revolutionizing the way business is done and is transforming society as a whole. As this technology advances further, the need to exploit detection and weakness awareness increases to prevent unauthorized access to critical resources and business functions, thereby rendering the system unavailable. Denial of Service (DoS) and Distributed DoS attacks are all too common. In this paper, we propose a Protocol Based Deep Intrusion Detection (PB-DID) architecture, in which we created a data-set of packets from IoT traffic by comparing features from the UNSWNB15 and Bot-IoT data-sets based on flow and Transmission Control Protocol (TCP). We classify non-anomalous, DoS, and DDoS traffic uniquely by taking care of the problems like imbalanced and over-fitting. We have achieved a classification accuracy of 96.3% by using deep learning (DL) technique.