Massive Failure Research Articles

NFV recovery strategies for critical services after massive failures in optical networks

Today, more critical services than ever rely on the communication infrastructure of 5G and beyond, demanding resilient recovery strategies when disasters occur. The inherent uncertainty of disasters makes post-disaster recovery a complex challenge. Today’s solutions focus on external infrastructure, such as alternative power supply or ad-hoc UAVs, to restore communication. However, the programmable nature introduced in 5G also allows us to migrate (relocate) Virtual Network Functions (VNFs) to restore communication more efficiently. In this paper, we develop an experimental framework to evaluate the performance of recovery strategies utilizing VNF migration in an optical network. We demonstrate that selecting the appropriate post-disaster recovery strategy can significantly accelerate the restoration of critical services by several hours in some disaster scenarios. Furthermore, we create ClusPRi, a modification of the virtual resource allocation algorithm ClusPR. ClusPRi prioritizes critical traffic when allocating resources in a post-disaster scenario. We show that adding routing priority to the resource allocation algorithm further accelerates the restoration of critical communication in a disaster scenario.

DRL-based progressive recovery for quantum-key-distribution networks

With progressive network recovery, operators restore network connectivity after massive failures along multiple stages, by identifying the optimal sequence of repair actions to maximize carried live traffic. Motivated by the initial deployments of quantum-key-distribution (QKD) over optical networks appearing in several locations worldwide, in this work we model and solve the progressive QKD network recovery (PQNR) problem in QKD networks to accelerate the recovery after failures. We formulate an integer linear programming (ILP) model to optimize the achievable accumulative key rates during recovery for four different QKD network architectures, considering different capabilities of using trusted relay and optical bypass. Due to the computational limitations of the ILP model, we propose a deep reinforcement learning (DRL) algorithm based on a twin delayed deep deterministic policy gradients (TD3) framework to solve the PQNR problem for large-scale topologies. Simulation results show that our proposed algorithm approaches well compared to the optimal solution and outperforms several baseline algorithms. Moreover, using optical bypass jointly with trusted relay can improve the performance in terms of the key rate by 14% and 18% compared to the cases where only optical bypass and only trusted relay are applied, respectively.

Community-led total sanitation (CLTS) implementation in West Mamprusi Municipal Assembly in Ghana. What do communities think eleven years on?

ObjectiveAccess to improved sanitation is a fundamental human right and an important aspect of Public Health. However, an estimated thousands of people in Ghana especially, the West Mamprusi Municipal Assembly (WMMA) still have no access to adequate toilet facilities. This has brought untold health repercussions to the inhabitants, the community, and the environment at large. To address this menace, the community-led total sanitation (CLTS) was implemented. This study aimed to assess communities’ perspectives on the implementation of CLTS and to understand the factors influencing its success and failures. MethodsA mixed-method approach involving sequential qualitative and quantitative methods was employed in this study. Participants for the quantitative study were randomly selected and surveyed using questionnaires. The qualitative study employed focus group discussion involving purposively sampled participants including assembly members, opinion leaders, and assembly staff. ResultsThe CLTS program in WMMA realized an apparent use of construction and proper use of household latrines leading to a reduction of open defecation free (ODF) and two communities achieving sanitized status in the history of the study area, enabling the training of latrine artisans and natural leaders to facilitate the CLTS expansion and sustainability, improved sanitation and hygiene, strengthened the enforcement of community rules and regulations and many others. ConclusionThe CLTS program has received more widespread acceptance in the study area than the previous government policy of constructing public toilets, which was greeted with massive failures due to poor implementation. To ensure that gains achieved through CLTS implementation are sustained longer, it is recommended that chiefs and opinion leaders should be involved in the CLTS programs to ensure checks and enforcement. The entrenchment of bylaws and more education to address enduring myths and misconceptions will sustain the program. Subsidies in the form of sanitation loans for latrine construction materials by the government and supporting non-governmental organizations (NGOs) will be paramount in sustaining ODF.

Lost in Translation: Why Are Rates of Hypertension Control Getting Worse Over Time?

Treatment of hypertension to decrease rates of cardiovascular disease is the most well studied and most broadly applicable treatment in cardiovascular prevention. Blood pressure can be measured anywhere, not just in a physician's office; medications are readily available, inexpensive, and have highly favorable benefit/harm ratios with relatively minimal side effects; and stepped medication regimens can be prescribed in algorithmic fashion by a variety of practitioners. Yet overall hypertension control rates in the United States have never exceeded 60%, and the last 5-10 years have seen decreased, rather than increased, rates of control. Here, I describe the scale of this massive failure to deliver on the promise of preventive hypertension care; outline the populations most affected and the contemporaneous events that have impacted hypertension control; discuss the disparate paths of hypertension science and health care delivery; and highlight novel interventions, approaches, and future opportunities to bend the curve back toward improvements in hypertension control.

The Teaching Methodology and the Behavior of Ordinary Secondary School Students in Learning Mathematics Subject: A case of selected Ordinary Secondary Schools in Mbeya, Tanzania

The study investigated the teaching methodology and the behavior of ordinary secondary school students in learning mathematics. This study sought to find behind the scenes why most students in ordinary secondary schools dislike mathematics, which leads to massive failures. To uncover this gap, the study applied a correlation research design. Systematic sampling technique of the interval 50th was used in which 100 respondents were selected; 20 respondents each from 5 selected secondary schools in Mbeya. Data were collected through a questionnaire. Data were analyzed descriptively and speculatively. The survey found that teaching materials/media were effectively implemented. Also, the findings indicate the non-adoption of informal behavior and non-reflection of mathematics teachings to the learner’s natural home environment. Thus, from these discrepancies, the study recommends that mathematics teachers be used to teaching simulation and visual aids/media. It is recommended that mathematics teachers use informal behavior such as courage words, remedial classes, and others for students adapted to mathematics-solving behavior. Lastly, it is suggested that mathematics teachings should be reflexive to students’ real-life environment.

Making group-work work: Navigating conflict and encouraging collaborative revision

Group work, especially for comprehensive class projects, is ubiquitous in higher education, yet despised by many students. In college, many students simply do not learn how to interact when in groups and how to collaborate effectively. Furthermore, by limiting student assessment of group work solely to a final project grade, students do not have the opportunity to collaboratively reflect on feedback and revise. Inspired by the massive failure of group comprehensive projects in my bioacoustics course, I will share tips I learned to navigate intra-group conflict, provide students with critical feedback on work at 3 key periods throughout the course, encourage collaborative revision, and engage with other groups via peer feedback.

Geomorphological characteristics and the kinematic process of the Ganheba rock–ice avalanche in Yulong Mountain, China

Rock–ice avalanches have increased in recent years due to global warming. On 12 March 2004, a massive failure of rock mass (9.1×106 m3) originated on the south slope of Yulong Mountain in Yunnan Province and eventually formed the Ganheba rock–ice avalanche, with an H/L ratio of 0.4. In this study, the geomorphological characteristics, sedimentary characteristics, and emplacement process of the Ganheba rock–ice avalanche were analyzed based on remote sensing interpretation, field investigation, and 2D discrete element modeling. This study suggests that long-term effects, including historical seismic effects and freeze–thaw action, were the key factors in the occurrence of this landslide. Interesting landforms and sedimentary structures found in this case, such as lateral ridges, superelevation, and boat rocks, were used to explain the characteristics of the velocity and the thinning spreading process of the avalanche mass. The numerical simulation further revealed that the entire movement of this rock–ice avalanche lasted about 105 s, with a maximum front velocity of 82 m/s. The underlying substrate rather than the ice is considered to have contributed to the hypermobility of the Ganheba rock–ice avalanche. The developed fissures, complex topography, and basal friction were determined to control the progressive fragmentation in this case. Meanwhile, the kinematic process of the Ganheba rock–ice avalanche was divided into four stages: failure and acceleration, collision deceleration, deceleration spreading, and deformation. The findings of this study contribute to an understanding of the evolution of glacier-related hazards in the high-mountain region.

Radical Participatory Design

Design has been a massive failure. It has functioned in the service of industry and capitalism, leaving us a world with several crises which we are failing to resolve. The onto-epistemic framework out of which this type of design injustice emerges is coloniality, highlighting a trans-locally experienced truth: our ontologies are our epistemologies. And our onto-epistemologies are our namologies–studies, perspectives, types, or ways of designing. If we instead embody an onto-epistemic framework of relationality, our design process becomes radically participatory. Radical Participatory Design (RPD) is meta-methadology that is participatory to the root or core. Using the models “designer as community member,” “community member as designer,” and “community member as facilitator,” RPD prioritizes relational, cultural, and spiritual knowledge, as well as lived experiential knowledge, over mainstream, institutional knowledge. Based on the experiential knowledge of employing radical participatory design over many years, we have induced a characteristic definition of RPD. Through an awareness of participation, we discuss the various benefits of RPD including genuine inclusion, true human-centeredness, moving beyond human-centeredness, embedded empathy, trauma-responsive design, and systemic action. We discuss the ethics of Radical Participatory design from both an equality and equity perspective. We offer ways of evaluating the success of the radically participatory design process. Lastly, we discuss the barriers and ways we have overcome them in our projects.

A Robust Fault Diagnosis Scheme using Deep Learning for High Voltage Transmission Line

The transmission lines repeatedly face an aggregation of shunt-faults and its impact in the real time system increases the vulnerability, damage in load, and line restoration cost. Fault detection in power transmission lines have become significantly crucial due to a rapid increase in number and length. Any kind of interruption or tripping in transmission lines can result in a massive failure over a large area, which necessitates the need of effective protection. The diagnosis of faults help in detecting and classifying transients that eventually make the protection of transmission lines convenient. In this paper, we propose a deep learning-enabled technique for the detection and classification of transmission line faults. The faulty information are extracted using Discrete Wavelet Transform (DWT) and fed into the multilayer perceptron classification model. The results indicate that the proposed approach is capable of accurately classifying and detecting faults in transmission line with high precision.

Bank Portfolio Allocation Strategy and Its Probability of Failure: Case of the Russian Banking Sector Purge

This paper aims to discover portfolio allocation strategies that facilitate a bank’s stability. The paper examines the phenomenon of massive failures of Russian banks in the period from 2013 to 2019, in order to identify which of the banks’ strategic decisions regarding assets and liabilities, as well as portfolio structure, lead to higher stability. The dataset contains financial indicators and prudential ratios of 895 commercial banks operating in Russia during that period. 507 banks, or 57% of all banks, lost their license during the considered period. Cases of bank failures were classified depending on whether the Central Bank identified any illegal activities conducted by the failed bank. The high failure rate provides an opportunity to study the differences between failed and non-failed banks in order to determine the factors associated with lowerfailure probability. Following the approach applied in most of the previous studies, we use a logistic regression to model the effect of different asset and liability portfolio structure on the failure probability. The hypothesis that failure probability of a bank is affected by its strategic focus of forming an assets and liabilities portfolio was statistically confirmed. We found that the focus of a bank’s activity on providing loans to individuals and attracting deposits from companies leads to lower failure probability, confirming the results of previous studies. Also, we found that more active cooperation with other banks in terms of both borrowing and lending is associated with lower failure probability. Furthermore, we found that banks are less likely to borrow from or lend money to their fellow banks that later fail with illegal activity accusations.Finally, we found that unlike the EU banks, Russian banks with higher profitability ratios are more stable. The results are relevant for industry practitioners in facilitating the development of a more resilient bank strategy, as well as for regulators for incorporation in early warning models.

FaaScinating Resilience for Serverless Function Choreographies in Federated Clouds

Cloud applications often benefit from deployment on serverless technology Function-as-a-Service (FaaS), which may instantly spawn numerous functions and charges users for the period when serverless functions are running. Maximum benefit is achieved when functions are orchestrated in a workflow or function choreographies (FCs). However, many provider limitations specific for FaaS, such as maximum concurrency or duration often increase the failure rate, which can severely hamper the execution of entire FCs. Current support for resilience is often limited to function retries or try-catch, which are applicable within the same cloud region only. To overcome these limitations, we introduce rAFCL, a middleware platform that maintains reliability of complex FCs in federated clouds. In order to support resilient FC execution under rAFCL, our model creates an alternative strategy for each function based on the required availability specified by the user. Alternative strategies are not restricted to the same cloud region, but may contain alternative functions across five providers, invoked concurrently in a single alternative plan or executed subsequently in multiple alternative plans. With this approach, rAFCL offers flexibility in terms of cost-performance trade-off. We evaluated rAFCL by running three real-life applications across three cloud providers. Experimental results demonstrated that rAFCL outperforms the resilience of AWS Step Functions, increasing the success rate of entire FC by 53.45%, while invoking only 3.94% more functions with zero wasted function invocations. rAFCL significantly improves availability of entire FCs to almost 1 and survives even after massive failures of alternative functions.

A child with genetic FN1 mutation in the absence of classic glomerulopathy with fibronectin deposits(GFND) findings on biopsy

BackgroundGlomerulopathy with fibronectin deposits (GFND) is a rare autosomal dominant genetic disorder, and proteinuria and hematuria are the most common clinical manifestations. The pathogenesis of this disease is primarily related to mutation of the fibronectin 1 gene. Unfortunately, without specific treatment, the prognosis remains poor. Here we present a case report that investigates the clinical characteristics, renal pathology, and gene testing of childhood GFND.Case presentationA two-year-old child was brought to our hospital for “persistent hematuria for 1 year and 10 months.” The disease onset was at the age of 4 months, with persistent microscopic hematuria accompanied by intermittent gross hematuria, occasionally with proteinuria, and without hypertension or renal failure. The chief complaint was intermittent gross hematuria, without massive proteinuria, hypertension, or renal failure. Family history: The child’s mother had microscopic hematuria, his maternal aunt had nephrotic syndrome due to focal segmental glomerulosclerosis, and his maternal grandmother had end-stage renal disease. No significant pathological changes were found in the renal pathological biopsy of the child under a light microscope. Under the electron microscope, the basement membrane was found to be of uneven thickness, ranging from 150 to 400 nm. The stratum compactum of the basement membrane was thickened, with a small part showing tear-like and cobweb-like morphology. No electron-dense deposits were found. The renal tubular epithelial cells were vacuolated, and there were no unique pathological changes in the renal interstitium. Immunofluorescence showed that IgG, IgM, IgA, C3, and C1q were all negative. Alport syndrome was preliminarily considered. However, exome sequencing revealed a mutated site in the fibronectin 1 gene. The child’s mother was the carrier of the pathogenic gene and the final diagnosis was GFND.ConclusionsFibronectin deposition is a typical pathological change in GFND, and the disease progresses slowly to end-stage renal disease. There is no specific treatment so far, and the prognosis is poor. The early onset of childhood patients may not show typical renal pathological changes, but only changes in the thickness of basement membrane, etc. Genome sequencing technology may helpful for the early diagnosis of GFND.

Mt. Rainier Sanctification

Mt. Rainier Sanctification

Explant analysis and implant registries are both needed to further improve patient safety.

In the early days of total joint replacement, implant fracture, material problems and wear presented major problems for the long-term success of the operation.Today, failures directly related to the implant comprise only 2–3% of the reasons for revision surgeries, which is a result of the material and design improvements in combination with the standardization of pre-clinical testing methods and the post-market surveillance required by the legal regulation.Arthroplasty registers are very effective tools to document the long-term clinical performance of implants and implantation techniques such as fixation methods in combination with patient characteristics.Revisions due to implant failure are initially not reflected by the registries due to their small number.Explant analysis including patient, clinical and imaging documentation is crucial to identify failure mechanisms early enough to prevent massive failures detectable in the registries.In the past, early reaction was not always successful, since explant analysis studies have either been performed late or the results did not trigger preventive measures until clinical failures affected a substantial number of patients.The identification of implant-related problems is only possible if all failures are reported and related to the number of implantations.A system that analyses all explants from revisions attributed to implant failure is mandatory to reduce failures, allowing improvement of risk assessment in the regulatory process.

Estimating the Tail Index of Conditional Distribution of Asset Returns

Massive stock market failures in the past decades cast a doubt on the standard normality assumption of many economic models. Despite decent research on the non-Gaussian characteristics of many financial time series, the question of tail heaviness still remains open. We conduct diagnostic analysis on the conditional distribution of asset returns of small/large companies (Russell 2000 and S&P 500) to look for clear evidence on the presence of heavy tails. We employ extreme value (EVT) tools in order to estimate the shape parameter () of Generalized Pareto distribution (GPD) using a well-known “Hill estimator”. It turns out that the shape parameter lies in the interval implying that the conditional distribution of asset returns supposedly has finite mean and variance. We also find an evidence that the tail estimates experience structural breaks during 2008 Global Financial Crisis.

Progressive Slice Recovery With Guaranteed Slice Connectivity After Massive Failures

In presence of multiple failures affecting their network infrastructure, operators are faced with the Progressive Network Recovery (PNR) problem, i.e., deciding the best sequence of repairs during recovery. With incoming deployments of 5G networks, PNR must evolve to incorporate new recovery opportunities offered by network slicing. In this study, we introduce the new problem of Progressive Slice Recovery (PSR), which is addressed with eight different strategies, i.e., allowing or not to change slice embedding during the recovery, and/or by enforcing different versions of slice connectivity (i.e., network vs. content connectivity). We propose a comprehensive PSR scheme, which can be applied to all recovery strategies and achieves fast recovery of slices. We first prove the PSR’s NP-hardness and design an integer linear programming (ILP) model, which can obtain the best recovery sequence and is extensible for all the recovery strategies. Then, to address scalability issues of the ILP model, we devise an efficient two-phases progressive slice recovery (2-phase PSR) meta-heuristic algorithm, small optimality gap, consisting of two main steps: i) determination of recovery sequence, achieved through a linear-programming relaxation that works in polynomial time; and ii) slice-embedding recovery, for which we design an auxiliary-graph-based column generation to re-embed failed slice nodes/links to working substrate elements within a given number of actions. Numerical results compare the different strategies and validate that amount of recovered slices can be improved up to 50% if operators decide to reconfigure only few slice nodes and guarantee content connectivity.

Fracture growth leading to mechanical spalling around deposition boreholes of an underground nuclear waste repository

This study presents a three-dimensional numerical analysis of multiple fracture growth leading to spalling around nuclear waste deposition boreholes. Mechanical spalling due to stress amplification after drilling is simulated using a finite element-based fracture growth simulator. Fractures initiate in tension based on a damage criterion and grow by evaluating stress intensity factors at each fracture tip. Tip propagation is multi-modal, resulting in final fracture patterns that are representative of both tensile and shear failure. Their geometries are represented by smooth parametric surfaces, which evolve during growth using lofting. The corresponding surface and volumetric meshes are updated at every growth step to accommodate the evolving fracture geometries. The numerical model is validated by comparing simulated fracture patterns against those observed in the AECL Underground Rock Laboratory Mine-By Experiment. It is subsequently calibrated to simulate fracture initiation and growth around boreholes drilled in the Forsmark granodiorite, subjected to a far-field anisotropic triaxial stress that corresponds to the in situ stress model from the Swedish Forsmark site. The deposition tunnel is implicitly simulated by attaching the deposition borehole to a free domain boundary. Several geomechanical cases are investigated, in which fracture growth is numerically evaluated as a function of in situ stress state, tunnel orientation, borehole geometry, total number of boreholes and borehole spacing. Numerical results show that spalling occurs in all cases, given the underground conditions at Forsmark, with borehole geometry, spacing and stresses affecting the extent of fracture nucleation and growth patterns. The uncertainty in underground stress conditions is evaluated through varying stress magnitudes and orientations relative to the tunnel floor. Whereas tunnel orientation influences the relative locations where fractures initiate with respect to the tunnel floor, fracture growth and its final extent is determined by the relative magnitudes of the in situ stresses. Higher stress differential causes higher spalling depths, but in all cases, failure extent is localised to the borehole vicinity, not exceeding one borehole radius. The cylindrical borehole is modified at the top to provide an access ramp for the spent fuel canisters and fracture growth around several deposition boreholes is simulated for borehole tops having cylindrical, conical, and wedge shapes. The enlargement of the borehole top induces higher stress concentrations at the borehole–tunnel junction, increasing the severity of spalling closer to the tunnel floor. Massive failure occurs when a multiple borehole model is considered and the inter-borehole distance is small enough that adjacent “spalled” areas interact. At Forsmark, through-going fractures are predicted to develop when the borehole spacing is less than 4 m. The effect of spalling on the structural integrity of the deposition boreholes is illustrated for each test case and quantified in terms of maximum spalling depth, spalling width and total fractured surface area.

Recognizing megatsunamis in Mediterranean deep sea sediments based on the massive deposits of the 365 CE Crete\xa0event

The Mediterranean Sea hosts two subduction systems along the convergent Africa-Eurasia plate boundary that have produced strong ground shaking and generated tsunamis. Based on historical descriptions and sedimentary records, one of these events, in 365 CE, impacted a broad geographical area, including tsunami evidence for distances of 700–800 km from the source event, qualifying it as a ‘megatsunami’. Understanding how megatsunamis are produced, and where they are more likely, requires a better understanding of the different secondary processes linked to these events such as massive slope failures, multiple turbidity current generation, and basin seiching. Our sedimentary records from an extensive collection of cores located in distal and disconnected basins, identify turbidites which are analyzed using granulometry, elemental (XRF), micropaleontological, and geochemical data in order to reconstruct their coastal or marine source. The results show that the 365 CE basin floor sediments are a mixture of inner shelf and slope materials. The tsunami wave produced multiple far-field slope failures that resulted in stacked basal turbidites. It also caused transport of continent-derived organic carbon and deposition over basal turbidites and into isolated basins of the deep ocean. The composition of sediment in isolated basins suggests their deposition by large-scale sheet like flows similar to what has been caused by the Tohoku earthquake associated tsunamis. This is significant for rectifying and resolving where risk is greatest and how cross-basin tsunamis are generated. Based on these results, estimates of the underlying deposits from the same locations were interpreted as possible older megatsunamis.

A Dynamic Distributed Deterministic Load-Balancer for Decentralized Hierarchical Infrastructures

In this work, we propose D3-Tree, a dynamic distributed deterministic structure for data management in decentralized networks, by engineering and extending an existing decentralized structure. Conducting an extensive experimental study, we verify that the implemented structure outperforms other well-known hierarchical tree-based structures since it provides better complexities regarding load-balancing operations. More specifically, the structure achieves an O(logN) amortized bound (N is the number of nodes present in the network), using an efficient deterministic load-balancing mechanism, which is general enough to be applied to other hierarchical tree-based structures. Moreover, our structure achieves O(logN) worst-case search performance. Last but not least, we investigate the structure’s fault tolerance, which hasn’t been sufficiently tackled in previous work, both theoretically and through rigorous experimentation. We prove that D3-Tree is highly fault-tolerant and achieves O(logN) amortized search cost under massive node failures, accompanied by a significant success rate. Afterwards, by incorporating this novel balancing scheme into the ART (Autonomous Range Tree) structure, we go one step further to achieve sub-logarithmic complexity and propose the ART+ structure. ART+ achieves an O(logb2logN) communication cost for query and update operations (b is a double-exponentially power of 2 and N is the total number of nodes). Moreover, ART+ is a fully dynamic and fault-tolerant structure, which supports the join/leave node operations in O(loglogN) expected WHP (with high proability) number of hops and performs load-balancing in O(loglogN) amortized cost.

The True Mechanisms Behind Immune Checkpoint Inhibitor Therapy for Cancer

Immune Checkpoint Inhibitor (ICI) therapy is the most exciting development in cancer treatments in recent years. As of the end of 2021, more than a hundred of clinical trials have been carried out by several major drug makers and research hospitals all over the world just to explore the use of ICI antibodies in almost every type of cancer and under various clinical settings. These clinical trials have resulted waves of good news in every year’s major academic conferences and FDA approvals, and now ICI therapy is in the move to take over traditional therapy to become the major player in clinical management of cancer. On the other hand, most of these clinical trials have failed to show clear benefits in most cancer patients, and only few have been reported in public. In real-world clinical setting, ICI antibodies are being massively and sometimes abusively prescribed for almost every desperate situation with clear clinical benefit in only a few (<10%). Yet, the enthusiasm behind ICI therapy is not dampened by the massive clinical failure but has been growing. The reason for the consistent enthusiasm among clinicians and patients is the miracle-like clinical responses seen in some of the responders that even including late-stage hopeless cases. Every clinician wants to repeat this miracle in the next seemingly identical patient, and every patient and their family members want to believe that they are in line for that miracle. But the reality is disheartening in that clinicians do not see the predictable repeat of miracle-like responses in seemingly identical patients and most patients selecting ICI therapy as the last straw in life did not benefit from it, if not hurt by it. What then are the reasons that ICI therapy is so impressive when working and so unpredictable in responses? This review attempts to draw some mechanistic aspects based on our own experiences in ICI therapy and to come up with a different explanation for the unexplained clinical observations. The goal of this review is to alert the clinical field about the danger and irreversible damages that wrongly used ICI antibodies may cause, and at the same time to introduce some preliminary criteria to select proper patient for the benefits and to avoid the harms of ICI therapy.